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@article{Bares_1989_1431,
author = "John Bares and Martial Hebert and Takeo Kanade and Eric Krotkov and Tom Mitchell and Reid Simmons and William Red L. Whittaker",
title = "Ambler: An Autonomous Rover for Planetary Exploration",
journal = "IEEE Computer",
month = "June",
year = "1989",
volume = "22",
number = "6",
pages = "18-26",
pdf="http://www.ri.cmu.edu/pub_files/pub2/bares_john_1989_1/bares_john_1989_1.pdf" 
}

@inproceedings{Caillas_1989_3552,
author = "C. Caillas and Martial Hebert and Eric Krotkov and In So Kweon and Takeo Kanade",
title = "Methods for Identifying Footfall Positions for a Legged Robot",
booktitle = "Proceedings of the IEEE/RSJ International Workshop on Intelligent Robots and Systems '89. The Autonomous Mobile Robots and Its Applications, (IROS '89)",
month = "September",
year = "1989",
pages = "244 - 250" 
}

@incollection{Choi_1990_4220,
author = "T. Choi and H. Delingette and M. DeLuise and Y. Hsin and Martial Hebert and Katsushi Ikeuchi",
title = "A perception and manipulation system for collecting rock samples",
year = "1990",
pdf="http://www.ri.cmu.edu/pub_files/pub3/choi_t_1990_1/choi_t_1990_1.pdf" 
}

@article{Cuschieri_1990_4274,
author = "J.M. Cuschieri and Martial Hebert",
title = "Three-Dimensional Map Generation From Side-Scan Sonar Images",
journal = "Journal of Energy Resources Technology",
month = "June",
year = "1990",
volume = "112",
pdf="http://www.ri.cmu.edu/pub_files/pub3/cuschieri_j_m_1990_1/cuschieri_j_m_1990_1.pdf",
abstract="The generation of three-dimensional (3-D) images and map building are essential components in the development of an autonomous underwater system. Although the direct generation of 3-D images is more efficient than the recovery of 3-D data from 2-D idormation, at present for underwater applications where sonar is the main form of remote sensing, the generation of 3-D images can only be achieved by either complex sonar systems or with systems which have a rather low resolution. In this paper an overview is presented on the type of sonar systems that are available for underwater remote sensing, and then a technique.is presented which demonstrates how through simple geometric reasoning procedures, 3-D information can be recoved from side scan-type (2-D) data. Also presented is the procedure to perform map building on the estimated 3-D data" 
}

@inproceedings{Cuschieri_1988_4275,
author = "J.M. Cuschieri and Martial Hebert",
title = "Sonar Applications for Underwater Vision",
booktitle = "The Eleventh Annual Energy-Sources Technology Conference and Exhibition - Current Practices and New Technology in Ocean Engineering - 1988",
month = "January",
year = "1988",
publisher = "The Ocean Engineering Division, ASME",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/cuschieri_j_m_1988_1/cuschieri_j_m_1988_1.pdf" 
}

@inproceedings{Delingette_1993_1350,
author = "H. Delingette and Martial Hebert and Katsushi Ikeuchi",
title = "A Spherical Representation for the Recognition of Curved Objects",
booktitle = "International Conference on Computer Vision",
month = "May",
year = "1993",
pages = "103 - 112",
pdf="http://www.ri.cmu.edu/pub_files/pub3/delingette_h_1993_1/delingette_h_1993_1.pdf",
abstract="The authors introduce a surface representation for recognizing curved objects. The approach begins by representing an object by a discrete mesh of points built from range data or from a geometric model of the object. The mesh is computed from the data by deforming a standard shaped mesh, for example, an ellipsoid, until it fits the surface of the object. Local regularity constraints that the mesh must satisfy are defined. A canonical mapping is then defined between the mesh describing the object and a standard spherical mesh. A surface curvature index which is pose-invariant is stored at every node of the mesh. This object representation is used for recognition by comparing the spherical model of a reference object with the model extracted from a new observed scene. It is shown that the similarity between reference model and observed data can be evaluated, and it is also demonstrated that the pose of the reference object in the observed scene can be easily computed using this representation." 
}

@article{Delingette_1992_4223,
author = "H. Delingette and Martial Hebert and Katsushi Ikeuchi",
title = "Shape representation and image segmentation using deformable surfaces",
journal = "Image and Vision Computing",
year = "1992",
pages = "132 - 145",
pdf="http://www.ri.cmu.edu/pub_files/pub3/delingette_h_1992_1/delingette_h_1992_1.pdf",
abstract="We present a technique for constructing shape representation from images using free-form deformable surfaces. We model an object as a closed surface that is deformed subject to attractive fields generated by input data points and features. Features affect the global shape of the surface or unstructured environments. The algorithm is general in that it makes few assumptions on the type of features, the nature of the data and the type of objects. We present results in a wide range of applications: reconstruction of smooth isolated objects such as human faces, reconstruction of structured objects such as polyhedra, and segmentation of complex scenes with mutually occluding objects. We have successfully tested the algorithm using data from different sensors including grey-coding range finders and video cameras, using one or several images." 
}

@techreport{Delingette_1992_4248,
author = "Herve Delingette and Martial Hebert and Katsushi Ikeuchi",
title = "Representation and Recognition of Free-Form Surfaces",
institution = "Computer Science Department, Carnegie Mellon University",
month = "November",
year = "1992",
number = "CMU-CS-92-214",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub3/delingette_herve_1992_1/delingette_herve_1992_1.pdf",
abstract="We introduce a new surface representation for recognizing curved objects. Our approach begins by representing an object by a discrete mesh of points built from range data or from a geometric model of the object The mesh is computed from the data by deforming a standard shaped mesh, for example, an ellipsoid, until it fits the surface of the object. We define local regularity constraints that the mesh must satisfy. We then define a canonical mapping between the mesh describing the object and a standard spherical mesh. A surface curvature index that is pose-invariant is stored at every node of the mesh. We use this object representation for recognition by comparing the spherical model of a reference object with the model extracted from a new observed scene. We show how the similarity between reference model and observed data can be evaluated and we show how the pose of the reference object in the observed scene can be easily computed using this representation. We present results on real range images which show that this approach to modelling and recognizing three-dimensional objects has three main advantages: First, it is applicable to complex curved surfaces that cannot be handled by conventional techniques. Second, it reduces the recognition problem to the computation of similarity between spherical distributions; in particular, the recognition algorithm does not require any combinatorial search. Finally, even though it is based on a spherical mapping, the approach can handle occlusions and partial views." 
}

@inproceedings{Delingette_1991_4235,
author = "H. Delingette and Martial Hebert and Katsushi Ikeuchi",
title = "Trajectory Generation with Curvature Constraint based on Energy Minimization",
booktitle = "Proceedings 1991 IEEE/RSJ International Conference On Intelligent Robotic Systems (IROS '91",
month = "November",
year = "1991",
pdf="http://www.ri.cmu.edu/pub_files/pub3/delingette_h_1991_1/delingette_h_1991_1.pdf" 
}

@inproceedings{Fitzpatrick_1992_2051,
author = "Kerien Fitzpatrick and Martial Hebert and Dean Pomerleau and Hagen Schempf",
title = "Autonomous Cargo Transport System",
booktitle = "Proceedings of the United States Postal Service 5th Advanced Technology Conference",
month = "December",
year = "1992" 
}

@inproceedings{Francois_1991_4279,
author = "C. Francois and Katsushi Ikeuchi and Martial Hebert",
title = "A Three-Finger Gripper for Manipulation in Unstructured Environments",
booktitle = "Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '91)",
month = "April",
year = "1991",
pages = "2261 - 2265",
pdf="http://www.ri.cmu.edu/pub_files/pub3/francois_c_1991_1/francois_c_1991_1.pdf",
abstract="This paper describes a gripper for manipulation in natural, un-structured environments. The specific manipulation task is to plck up surface material such as pebbles, or small rocks, in a natural terrain. The application is to give autonomous sampling capabilities to an autonomous vehicle for planetary exploration. We describe the task analysis process that led to the selection of a configuration with three "soft" fingers. We carry out a complete analysis of the stability of a grasp for this gripper including an analysis of the deformation of the fingers at the points of contact. Finally. we describe the implementation of a grasp selection algorithm and present results on three-dimensional representations of objects computed from range data." 
}

@inproceedings{Gowdy_1990_1228,
author = "Jay Gowdy and Anthony (Tony) Stentz and Martial Hebert",
title = "Hierarchical Terrain Representations for Off-Road Navigation",
booktitle = "Proceedings of SPIE Symposium on Mobile Robots",
year = "1990",
pdf="http://www.ri.cmu.edu/pub_files/pub3/gowdy_jay_1990_1/gowdy_jay_1990_1.pdf",
abstract="For most autonomous land vehicle tasks, creating the terrain representation is the greatest part of the problem. For example, once a road following system represents the terrain presented to it as road and non-road it is relatively easy to plan a path through the terrain. However, off road navigation does not have the luxury of such a compact representation. An off-road planner needs a detailed map of the terrain, and needs an efficient way of querying that terrain map. We have implemented a system that satisfies these two constraints for off-road navigation. We first build a Cartesian elevation map from a series of laser range finder images. This map is a complete, but intractable, representation of the terrain. We use the map to build a hierarchical representation of the terrain that we call a "terrain pyramid." Each cell at a level of the terrain pyramid holds the maximum and minimum elevation of the four cells in the !evel below it. We also build pyramids for various features in the Cartesian map such as terrain discontinuity and slope. The terrain pyramids are shipped to a planner module. We provide the planner module with calls to find the minimum and maximum values of a feature over any rectangle in the terrain. With these calls taking advantage of the hierarchical representation of the terrain. the planner can efficiently determine a safe path through the terrain." 
}

@inproceedings{Hebert_1994_1666,
author = "Martial Hebert",
title = "Pixel-Based Processing for Autonomous Driving",
booktitle = "Proc. International Conference on Robotics and Automation",
month = "May",
year = "1994",
pdf="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1994_1/hebert_martial_1994_1.pdf" 
}

@inproceedings{Hebert_1989_4251,
author = "Martial Hebert",
title = "Building and navigating maps of road scenes using an active sensor",
booktitle = "Proceedings of IEEE International Conference on Robotics and Automation (ICRA '89)",
month = "May",
year = "1989",
pages = "1136 - 1143",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1989_1/hebert_martial_1989_1.pdf" 
}

@inproceedings{Hebert_1989_4252,
author = "Martial Hebert",
title = "Terrain Modeling for Autonomous Underwater Navigation",
booktitle = "Proceedings of the 7th International Symposium on Unmanned Untethered Submersible Technology",
month = "June",
year = "1989",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1989_2/hebert_martial_1989_2.pdf" 
}

@inproceedings{Hebert_1989_2435,
author = "Martial Hebert and C. Caillas and Eric Krotkov and In So Kweon and Takeo Kanade",
title = "Terrain Mapping for a Roving Planetary Explorer",
booktitle = "Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '89)",
month = "May",
year = "1989",
volume = "2",
pages = "997-1002",
pdf="http://www.ri.cmu.edu/pub_files/pub2/hebert_martial_1989_2/hebert_martial_1989_2.pdf" 
}

@inproceedings{Hebert_1995_1747,
author = "Martial Hebert and R. Hoffman and Andrew Johnson and James Osborn",
title = "Sensor Based Interior Modeling",
booktitle = "American Nuclear Society 6th Topical Meeting on Robotics and Remote Systems (ANS '95)",
month = "February",
year = "1995",
pages = "731 - 737",
pdf="http://www.ri.cmu.edu/pub_files/pub1/hebert_martial_1995_1/hebert_martial_1995_1.pdf" 
}

@article{Hebert_1995_1069,
author = "Martial Hebert and Katsushi Ikeuchi and H. Delingette",
title = "A Spherical Representation for Recognition of Free-Form Surfaces",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
month = "July",
year = "1995",
volume = "17",
number = "7",
pages = "681-690",
pdf="http://www.ri.cmu.edu/pub_files/pub2/hebert_martial_1995_1/hebert_martial_1995_1.pdf",
abstract="Introduces a new surface representation for recognizing curved objects. The authors approach begins by representing an object by a discrete mesh of points built from range data or from a geometric model of the object. The mesh is computed from the data by deforming a standard shaped mesh, for example, an ellipsoid, until it fits the surface of the object. The authors define local regularity constraints that the mesh must satisfy. The authors then define a canonical mapping between the mesh describing the object and a standard spherical mesh. A surface curvature index that is pose-invariant is stored at every node of the mesh. The authors use this object representation for recognition by comparing the spherical model of a reference object with the model extracted from a new observed scene. The authors show how the similarity between reference model and observed data can be evaluated and they show how the pose of the reference object in the observed scene can be easily computed using this representation. The authors present results on real range images which show that this approach to modelling and recognizing 3D objects has three main advantages: (1) it is applicable to complex curved surfaces that cannot be handled by conventional techniques; (2) it reduces the recognition problem to the computation of similarity between spherical distributions; in particular, the recognition algorithm does not require any combinatorial search; and (3) even though it is based on a spherical mapping, the approach can handle occlusions and partial views." 
}

@inproceedings{Hebert_1988_2471,
author = "Martial Hebert and Takeo Kanade",
title = "3-D Vision for Outdoor Navigation by an Autonomous Vehicle",
booktitle = "Proceedings of the 1988 DARPA Image Understanding Workshop",
month = "April",
year = "1988",
pages = "593-601",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1988_2/hebert_martial_1988_2.pdf" 
}

@inproceedings{Hebert_1986_2428,
author = "Martial Hebert and Takeo Kanade",
title = "Outdoor Scene Analysis Using Range Data",
booktitle = "Proc. 1986 IEEE International Conference on Robotics and Automation",
month = "April",
year = "1986",
volume = "3",
pages = "1426-1432",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1986_1/hebert_martial_1986_1.pdf" 
}

@inproceedings{Hebert_1985_2466,
author = "Martial Hebert and Takeo Kanade",
title = "First Results on Outdoor Scene Analysis Using Range Data",
booktitle = "Proceedings of the 1985 DARPA Image Understanding Workshop",
year = "1985",
pages = "224-231" 
}

@techreport{Hebert_1988_175,
author = "Martial Hebert and Takeo Kanade and In So Kweon",
title = "3-D Vision Techniques for Autonomous Vehicles",
institution = "Robotics Institute, Carnegie Mellon University",
month = "August",
year = "1988",
number = "CMU-RI-TR-88-12",
address = "Pittsburgh, PA" pdf ="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1988_1/hebert_martial_1988_1.pdf" 
}

@inproceedings{Hebert_1993_4249,
author = "Martial Hebert and Eric Krotkov",
title = "Local Perception for Mobile Robot Navigation in Natural Terrain: Two Approaches",
booktitle = "Workshop on Computer Vision for Space Applications",
month = "September",
year = "1993",
pdf="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1993_1/hebert_martial_1993_1.pdf" 
}

@article{Hebert_1992_1429,
author = "Martial Hebert and Eric Krotkov",
title = "3-D Measurements from Imaging Laser Radars: How Good Are They?",
journal = "International Journal of Image and Vision Computing",
month = "April",
year = "1992",
volume = "10",
number = "3",
pages = "170-178",
pdf="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1992_1/hebert_martial_1992_1.pdf",
abstract="In this paper we analyse a class of imaging range finders - amplitude-modulated continuous-wave laser radars - in the context of computer vision and robotics. The analysis develops measurement models from the fundamental principles of laser radar operation, and identifies the nature and cause of key problems that affect measurements from this class of sensors. We classify the problems as fundamental (e.g. related to the signal-to-noise ratio), as architectural (e.g. limited by encoding distance by angles in [0, 2n]), and as artifacts of particular hardn*are implementations (e.g. insufficient temperature compensation). Experimental results from two different devices - scanning laser rangefinders designed for autonomous navigation - illustrate and support the analysis." 
}

@inproceedings{Hebert_1991_3654,
author = "Martial Hebert and Eric Krotkov",
title = "3-D measurements from imaging laser radars: how good are they?",
booktitle = "Proceedings of the IEEE/RSJ International Workshop on Intelligent Robots and Systems '91, Intelligence for Mechanical Systems",
month = "November",
year = "1991",
volume = "1",
pages = "359 - 364",
abstract="The authors analyze a class of imaging range finders-amplitude-modulated continuous-wave laser radars-in the context of computer vision and robotics. The analysis develops measurement models from the fundamental principles of laser radar operation, and identifies the nature and cause of key problems that plague measurements from this class of sensors. They classify the problems as fundamental (e.g. related to the signal-to-noise ratio), as architectural (e.g. limited by encoding distance by angles (0.2 pi )), and as artifacts of particular hardware implementations (e.g. insufficient temperature compensation). Experimental results from two different scanning laser range finders designed for autonomous navigation illustrate and support the analysis.",
pdf="http://www.ri.cmu.edu/pub_files/pub2/hebert_martial_1991_1/hebert_martial_1991_1.pdf" 
}

@inproceedings{Hebert_1989_2437,
author = "Martial Hebert and Eric Krotkov and Takeo Kanade",
title = "A Perception System for a Planetary Explorer",
booktitle = "Proc. of the 28th IEEE Conference on Decision and Control",
month = "December",
year = "1989",
volume = "2",
pages = "1151-1156",
pdf ="http://www.ri.cmu.edu/pub_files/pub2/hebert_martial_1989_1/hebert_martial_1989_1.pdf",
abstract="To perform planetary exploration without human supervision, a completely autonomous robot must be able to model its environment and to locate itself while exploring its surroundings. For that purpose, the authors propose a modular perception system for an autonomous explorer. The perception system maintains a consistent internal representation of the observed terrain from multiple sensor views. The representation can be accessed from other modules through queries. The perception system is intended to be used by the Ambler, a six-legged vehicle being built at the authors' university. A partial implementation of the system using a range scanner is presented as well as experimental results on a testbed that includes the sensor, one computer-controlled leg, and obstacles on a sandy surface." 
}

@inproceedings{Hebert_1987_1649,
author = "Martial Hebert and Charles Thorpe and S. Dunn and J. Cushieri and P. Rushfeldt and W. Girodet and P. Schweitzer",
title = "A Feasibility Study for Long Range Autonomous Underwater Vehicle",
booktitle = "Proceedings of Fifth International Symposium on Unmanned Untethered Submersible Technology",
month = "June",
year = "1987",
pages = "1-13",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/hebert_martial_1987_1/hebert_martial_1987_1.pdf" 
}

@inproceedings{Higuchi_1994_1668,
author = "K. Higuchi and H. Delingette and Martial Hebert and Katsushi Ikeuchi",
title = "Merging Multiple Views Using a Spherical Representation",
booktitle = "Proc of 2nd IEEE Workshop on CAD-based Vision",
month = "February",
year = "1994",
pages = "124 - 131",
pdf="http://www.ri.cmu.edu/pub_files/pub2/higuchi_k_1994_1/higuchi_k_1994_1.pdf",
abstract="This paper proposes a new method for building a 3-D model from a set of range images. The method can merge data of free-form surfaces obtained from arbitrary viewing directions, with no prior knowledge of the poses. Our approach is based on matching the spherical representations of an object between the views. To obtain the spherical representation, we deform a discrete mesh to fit the object surface. A variation of the Gaussian curvature metric, which we call simplex angle, is computed at each node on the deformed mesh and mapped to a coordinate on the unit sphere. The transformation of the objects is computed by comparing the simplex angle measure at each node on the unit sphere. The transformation which produces the minimum errors is selected as the best match. We have implemented this method, applied the method to range images of objects from arbitrary viewpoints, and demonstrated the applicability for modeling from observation." 
}

@article{Higuchi_1995_1068,
author = "K. Higuchi and Martial Hebert and Katsushi Ikeuchi",
title = "Building 3-D Models from Unregistered Ranges Images",
journal = "CVGIP-GMIP",
month = "July",
year = "1995",
volume = "57",
number = "4",
pages = "315-333",
pdf="http://www.ri.cmu.edu/pub_files/pub1/higuchi_k_1995_1/higuchi_k_1995_1.pdf" 
}

@inproceedings{Higuchi_1994_1667,
author = "K. Higuchi and Martial Hebert and Katsushi Ikeuchi",
title = "Building 3D models from Unregistered Range Images",
booktitle = "Proceedings of IEEE Conference on Robotics and Automation (ICRA '94)",
month = "May",
year = "1994",
volume = "3",
pages = "2248 - 2253",
pdf="http://www.ri.cmu.edu/pub_files/pub3/higuchi_k_1994_1/higuchi_k_1994_1.pdf",
abstract="The authors describe an approach to building a three-dimensional model from a set of range images. The authors' goal is to build models of free-form surfaces obtained from arbitrary viewing directions, with no initial estimate of the relative viewing directions. The approach is based on building discrete meshes representing the surfaces observed in each of the range images, to map each of the meshes to a spherical image, and to compute the transformations between the views by matching the spherical images. The meshes are built using an iterative fitting algorithm previously developed; the spherical images are built by matching the nodes of the surface meshes to the nodes of a reference mesh on the unit sphere and by storing a measure of curvature at every node. The authors describe the algorithms used for building such models from range images and for matching them. The authors give results obtained using range images of complex objects." 
}

@techreport{Higuchi_1993_1371,
author = "K. Higuchi and Martial Hebert and Katsushi Ikeuchi",
title = "Building 3-D Models from Unregistered Range Images",
institution = "Computer Science Department, Carnegie Mellon University",
month = "November",
year = "1993",
number = "CMU-CS-93-214",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub4/higuchi_k_1993_1/higuchi_k_1993_1.pdf",
abstract="Most computer vision systems require accurate three-dimensional models. The problem of building such models from observations consists in taking multiple range image of the object from different viewing positions and orientations, referred to as "viewing poses", to match the data in the different images in order to recover the relative poses, and to merge the data into a single model using the estimated poses. The approaches proposed so far suffer from two major limitations. First, they require accurate knowledge of the relative viewing poses. Second, they either require a complicated feature extraction algorithm to be applied to the range image or they restrict the class of shapes that can be modelled. Our goal in this paper is to eliminate these two restrictions in order to allow modelling of natural, free-form objects from arbitrary unknown viewpoints." 
}

@techreport{Higuchi_1993_1372,
author = "K. Higuchi and Martial Hebert and Katsushi Ikeuchi",
title = "Combining Shape and Color Information For 3D Object Recognition",
institution = "Computer Science Department, Carnegie Mellon University",
month = "December",
year = "1993",
number = "CMU-CS-93-215",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub1/higuchi_k_1993_2/higuchi_k_1993_2.pdf" 
}

@techreport{Ikeuchi_1995_2767,
author = "Katsushi Ikeuchi and Martial Hebert",
title = "Spherical Representations: from EGI to SAI",
institution = "Computer Science Department, Carnegie Mellon University",
month = "October",
year = "1995",
number = "CMU-CS-95-197",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub1/ikeuchi_katsushi_1995_1/ikeuchi_katsushi_1995_1.pdf" 
}

@inproceedings{Ikeuchi_1992_4228,
author = "Katsushi Ikeuchi and Martial Hebert",
title = "Task Oriented Vision",
booktitle = "Proceedings of the 1992 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '92)",
month = "May",
year = "1992",
pages = "2187 - 2194",
pdf="http://www.ri.cmu.edu/pub_files/pub3/ikeuchi_katsushi_1992_1/ikeuchi_katsushi_1992_1.pdf",
abstract="This paper overviews two recently completed vision systems (a rock sampling system for planetary rovers and a bin-picking system for industrial robots). Then, we will examine the reason why these two systems have different architectures although their goals are roughly same, picking up something by visual observation. Based on this discussion, we will develop the task-oriented vision paradigm, and examine the difference between the task-oriented vision paradigm and the traditional Marr's paradigm. We will also explore the research issues necessary for completing the task-oriented vision paradigm." 
}

@incollection{Johnson_1996_1698,
author = "Andrew Johnson and Martial Hebert",
title = "Seafloor Map Generation for Autonomous Underwater Vehicle Navigation",
booktitle = "Autonomous Robots",
pages = "145-168",
year = "1996",
volume = "3",
pdf="http://www.ri.cmu.edu/pub_files/pub1/johnson_andrew_1996_1/johnson_andrew_1996_1.pdf" 
}

@techreport{Johnson_1996_399,
author = "Andrew Johnson and Martial Hebert",
title = "Recognizing Objects by Matching Oriented Points",
institution = "Robotics Institute, Carnegie Mellon University",
month = "May",
year = "1996",
number = "CMU-RI-TR-96-04",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub2/johnson_andrew_1996_1/johnson_andrew_1996_1.pdf",
abstract="By combining techniques from geometric hashing and structural indexing, we have developed a new representation for recognition of free-form objects from three dimensional data. The representation comprises descriptive spin-images associated with each oriented point on the surface of an object. Constructed using single point bases, spin-images are data level shape descriptions that are used for efficient matching of oriented points. During recognition, scene spin-images are indexed into a stack of model images to establish point correspondences between a model object and scene data. Given oriented point correspondences, a rigid transformation that maps the model into the scene is calculated and then refined and verified using a modified iterative closest point algorithm. Indexing of oriented points bridges the gap between recognition by global properties and feature bases recognition without resorting to error-prone segmentation or feature extraction. It requires no knowledge of the initial transformation between model and scene, and it can register fully 3-D data sets as well as recognize objects from partial views with occlusions. We present results showing simultaneous recognition of multiple 3-D anatomical models in range images and range image registration in the context of interior modeling of an industrial facility. " 
}

@techreport{Johnson_1995_360,
author = "Andrew Johnson and Martial Hebert",
title = "Refinement of Seafloor Elevation Using Acoustic Backscatter",
institution = "Robotics Institute, Carnegie Mellon University",
month = "March",
year = "1995",
number = "CMU-RI-TR-95-01",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub3/johnson_andrew_1995_1/johnson_andrew_1995_1.pdf",
abstract="We propose an algorithm for the reconstruction of elevation and material property maps of the seafloor using a sidescan sonar backscatter image and sparse bathymetric points co-registered within the image. Given a path for the sensor, the reconstruction is corrected for the movement of the fish during the image generation process. To perform reconstruction, an arbitrary but computable scattering model is assumed for the seafloor backscatter. The algorithm uses the sparse bathymetric data to generate an initial estimate for the elevation map which is then iteratively refined to fit the backscatter image by minimizing a global error functional. Concurrently, the parameters of the scattering model are determined on a coarse grid in the image by fitting the assumed scattering model to the backscatter data. The elevation surface and the scattering parameter maps converge to their best fit shape and values given the backscatter data. The reconstruction is corrected for the movement of the sensor by initially doing local reconstructions in sensor coordinates and then transforming the local reconstructions to a global coordinate system and performing the reconstruction again. The algorithm supports different scattering models, so it can be applied to different underwater environments and sonar sensors. In addition to the elevation map of the seafloor, the parameters of the scattering model at every point in the image are generated. Since these parameters describe material properties of the seafloor, the maps of the scattering model parameters can be used to segment the seafloor by material type." 
}

@inproceedings{Johnson_1995_1008,
author = "Andrew Johnson and Patrick (Chris) Leger and R. Hoffman and Martial Hebert and James Osborn",
title = "3-D object modeling and recognition for telerobotic manipulation",
booktitle = "Proc. IEEE Intelligent Robots and Systems",
month = "August",
year = "1995",
volume = "1",
pages = "103 - 110",
pdf="http://www.ri.cmu.edu/pub_files/pub1/johnson_andrew_1995_1/johnson_andrew_1995_1.pdf",
abstract="This paper describes a system that semi-automatically builds a virtual world for remote operations by constructing 3-D models of a robot's work environment. With a minimum of human interaction, planar and quadric surface representations of objects typically found in man-made facilities are generated from laser rangefinder data. The surface representations are used to recognize complex models of objects in the scene. These object models are incorporated into a larger world model that can be viewed and analyzed by the operator, accessed by motion planning and robot safeguarding algorithms, and ultimately used by the operator to command the robot through graphical programming and other high level constructs. Limited operator interaction, combined with assumptions about the robots task environment, make the problem of modeling and recognizing objects tractable and yields a solution that can be readily incorporated into many telerobotic control schemes." 
}

@inproceedings{Kelly_1992_1220,
author = "Alonzo Kelly and Anthony (Tony) Stentz and Martial Hebert",
title = "Terrain Map Building for Fast Navigation on Rugged Outdoor Terrain",
booktitle = "Proceedings of SPIE Symposium on Mobile Robots",
year = "1992" 
}

@inproceedings{Krotkov_1989_2434,
author = "Eric Krotkov and C. Caillas and Martial Hebert and In So Kweon and Takeo Kanade",
title = "First Results in Terrain Mapping for a Roving Planetary Explorer",
booktitle = "Proc. NASA Conference on Space Telerobotics",
month = "January",
year = "1989",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/krotkov_eric_1989_1/krotkov_eric_1989_1.pdf" 
}

@inproceedings{Krotkov_1995_1752,
author = "Eric Krotkov and Martial Hebert",
title = "Mapping and Positioning for a Prototype Lunar Rover",
booktitle = "IEEE International Conference on Robotics and Automation",
month = "May",
year = "1995",
volume = "3",
pages = "2913-2919",
pdf="http://www.ri.cmu.edu/pub_files/pub2/krotkov_eric_1995_1/krotkov_eric_1995_1.pdf",
abstract="In this paper, we describe practical, effective approaches to outdoor mapping and positioning, and present results from systems implemented for a prototype lunar rover. For mapping, we have developed a binocular head and mounted it on a motion-averaging mast. This head provides images to a normalized correlation matcher, that intelligently selects what part of the image to process (saving time), and subsamples the images (again saving time) without subsampling disparities (which would reduce accuracy). The mapping system has operated successfully during long-duration field exercises, processing streams of thousands of images. The positioning system employs encoders, inclinometers, a compass, and a turn-rate sensor to maintain the position and orientation of the rover as it traverses. The system succeeds in the face of significant sensor noise by virtue of sensor modelling, plus extensive filtering and data screening." 
}

@inproceedings{Krotkov_1994_1725,
author = "Eric Krotkov and Martial Hebert and M. Buffa and Fabio Cozman and L. Robert",
title = "Stereo Driving and Position Estimation for Autonomous Planetary Rovers",
booktitle = "IARP Workshop on Robotics in Space",
month = "July",
year = "1994",
pdf="http://www.ri.cmu.edu/pub_files/pub3/krotkov_eric_1994_1/krotkov_eric_1994_1.pdf",
abstract="In this paper we present two new approaches to planetary rover perception. One approach concerns stereo driving without 3-D reconstruction. This approach begins with weakly calibrated stereo images, and evaluates the traversability of terrain using shape indicators such as relative slope and relative elevation. The approach then evaluates candidate paths based on the traversability analysis and generates the best path. The second approach involves estimating vehicle position by observing the Sun. At a given time, a measurement of the Sun's altitude constrains the observer to lie on a circle on the terrestrial surface called the circle of equal altitude. We determine the position of the observer by intersecting circles of equal altitude identified at different times. We are validating experimentally both approaches in unstructured, outdoor environments with several wheeled rovers, Future efforts will transfer the developed technology into Lunar Rover demonstration and flight programs." 
}

@article{krotkov-ar-1997,
author = "Eric Krotkov and Martial Hebert and Reid Simmons",
title = "Stereo Perception and Dead Reckoning for a Prototype Lunar Rover",
journal = "Autonomous Robots",
month = "December",
year = "1995",
volume = "2",
number = "4",
pages = "313-331",
pdf="http://www.ri.cmu.edu/pub_files/pub1/krotkov_eric_1995_1/krotkov_eric_1995_1.pdf" 
}

@incollection{Kweon_1985_4201,
author = "In So Kweon and Martial Hebert and Takeo Kanade",
title = "Sensor Fusion of Range and Reflectance Data for Outdoor Scene Analysis",
year = "1985",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/kweon_in_so_1985_1/kweon_in_so_1985_1.pdf" 
}

@incollection{Langer_1994_4253,
author = "Dirk Langer and Martial Hebert",
title = "Building Elevation Maps from Underwater Sonar Data",
year = "1994",
pdf="http://www.ri.cmu.edu/pub_files/pub3/langer_dirk_1994_2/langer_dirk_1994_2.pdf",
abstract="Deriving a terrain model from sensor data is an important task for the autonomous navigation of a mobile robot. This paper describes an approach for autonomous underwater vehicles using a side scan sonar system. First. some general aspects of the type of data and filtering techniques to improve it are discussed. We then proceed to derive an estimated bottom contour, using a geometric reflection model and information about shadows and highlights. Several techniques of surface reconstruction and their limitations are presented." 
}

@inproceedings{Langer_1991_4255,
author = "Dirk Langer and Martial Hebert",
title = "Building Qualitative Elevation Maps from Side Scan Sonar Data for Autonomous Underwater Navigation",
booktitle = "Proceedings of the 1991 IEEE International Conference on Robotics and Automation (ICRA '91)",
month = "April",
year = "1991",
pdf="http://www.ri.cmu.edu/pub_files/pub3/langer_dirk_1991_1/langer_dirk_1991_1.pdf",
abstract="Deriving a terrain model from sensor data is an important task for the autonomous navigation of a mobile robot. This paper describes an approach for autonomous underwater vehicles using a side scan sonar system. First. some general aspects of the type of data and filtering techniques to improve it are discussed. We then proceed to derive an estimated bottom contour, using a geometric reflection model and information about shadows and highlights. Several techniques of surface reconstruction and their limitations are presented. We also describe a method of feature extraction which is important for future data matching/fusion procedures." 
}

@article{Langer_1994_1070,
author = "Dirk Langer and Julio Rosenblatt and Martial Hebert",
title = "A Behavior-Based System for Off-Road Navigation",
journal = "IEEE Trans. Robotics and Automation",
month = "December",
year = "1994",
volume = "10",
number = "6",
pages = "776-782",
pdf="http://www.ri.cmu.edu/pub_files/pub1/langer_dirk_1994_1/langer_dirk_1994_1.pdf" 
}

@inproceedings{Langer_1994_1678,
author = "Dirk Langer and Julio Rosenblatt and Martial Hebert",
title = "A Reactive System For Off-Road Navigation",
booktitle = "Proc. of IEEE Robotics and Automation",
month = "May",
year = "1994",
pdf ="http://www.ri.cmu.edu/pub_files/pub3/langer_dirk_1994_1/langer_dirk_1994_1.pdf",
abstract="In this paper; we describe a core system for autonomous navigation in outdoor natural terrain. The system consists of three parts: a perception module which processes range images to identify untraversable regions of the terrain, a local map management module which maintains a representation of the environment in the vicinity of the vehicle, and a planning module which issues commands to the vehicle controller. Our approach is to use the concept of early traversability evaluation, in which the perception module decides which parts of the terrain are traversable as soon as a new image is taken, and on the use of reactive planning for generating commands to drive the vehicle. We argue that our approach leads to a robust and efficient navigation system. We illustrate our approach by an experiment in which a vehicle travelled autonomously for one kilometer through unmapped cross-country terrain. The system used in this experiment can be viewed as a core navigation system in that other modules, such as a map navigation module, can be easily added to the system." 
}

@inproceedings{Langer_1994_1677,
author = "Dirk Langer and Julio Rosenblatt and Martial Hebert",
title = "An Integrated System for Autonomous Off-Road Navigation",
booktitle = "Proc. IEEE Int. Conf. on Robotics and Automation",
month = "May",
year = "1994",
pdf="http://www.ri.cmu.edu/pub_files/pub1/langer_dirk_1994_2/langer_dirk_1994_2.pdf" 
}

@inproceedings{Nashman_1993_4610,
author = "M. Nashman and Henry Schneiderman",
title = "Real-time Visual Processing For Autonomous Driving",
booktitle = "Intelligent Vehicles '93 Symposium",
month = "July",
year = "1993",
pages = "373 - 378",
url ="http://www.ri.cmu.edu/pubs/pub_4610.html" 
}

@inproceedings{Neureuther_1996_1295,
author = "A.R. Neureuther and Owen Carmichael",
title = "Computer Intensive Problems in Simulation of Integrated Circuit Lithography and Topography",
booktitle = "Proceedings NASA AMES Workshop",
month = "March",
year = "1996",
url="http://www.ri.cmu.edu/pubs/pub_1295.html",
keywords="geometric modeling" 
}

@inproceedings{Ponce_1994_1685,
author = "J. Ponce and R. Bajcsy and D. Metaxas and T. Binford and D. Forsyth and Martial Hebert and Katsushi Ikeuchi and A. Kak and L. Shapiro and S. Sclaroff and A. Pentland and G. Stockman",
title = "Object representation for object recognition",
booktitle = "Proc of IEEE conf. on Computer Vision and Pattern Recognition",
month = "June",
year = "1994",
pages = "147-152",
pdf="http://www.ri.cmu.edu/pub_files/pub2/ponce_j_1994_1/ponce_j_1994_1.pdf" 
}

@inproceedings{Robert_1994_1688,
author = "L. Robert and M. Buffa and Martial Hebert",
title = "Weakly-Calibrated Stereo Perception for Rover Navigation",
booktitle = "Proc. Image Understanding Workshop",
month = "November",
year = "1994" 
}

@inproceedings{Robert_1994_1687,
author = "L. Robert and Martial Hebert",
title = "Deriving Orientation Cues from Stereo Images",
booktitle = "Proc. European Conference on Computer Vision",
month = "May",
year = "1994" 
}

@inproceedings{Schneiderman_1993_1032,
author = "Henry Schneiderman and J. Albus",
title = "Progress and Prospects for Vision-based Automatic Driving",
booktitle = "Proceedings of IVHS America 3rd Annual Meeting",
month = "April",
year = "1993",
url = "http://www.ri.cmu.edu/pubs/pub_1032.html" 
}

@inproceedings{Schneiderman_1991_1035,
author = "Henry Schneiderman and Pradeep Khosla",
title = "Implementation of Traded and Shared Control Strategies Using a Tactile Sensor",
booktitle = "Robotics and Remote Systems (Proceedings of the 4th ANS Topical Meeting)",
month = "February",
year = "1991",
url="http://www.ri.cmu.edu/pubs/pub_1035.html" 
}

@article{Schneiderman_1994_4609,
author = "Henry Schneiderman and M. Nashman",
title = "A discriminating feature tracker for vision-based autonomous driving",
journal = "IEEE Transactions on Robotics and Automation",
month = "December",
year = "1994",
volume = "10",
number = "6",
pages = "769 - 775",
url ="http://www.ri.cmu.edu/pubs/pub_4609.html",
abstract="A new vision-based technique for autonomous driving is described. This approach explicitly addresses and compensates for two forms of uncertainty: uncertainty about changes in road direction and uncertainty in the measurements of the road derived in each image. Autonomous driving has been demonstrated on both local roads and highways at speeds up to 100 km/h. The algorithm has performed well in the presence of non-ideal road conditions including gaps in the lane markers, sharp curves, shadows, cracks in the pavement, and wet roads. It has also performed well in rain, dark, and nighttime driving with headlights." 
}

@inproceedings{Schneiderman_1992_1031,
author = "Henry Schneiderman and M. Nashman",
title = "Visual Processing for Autonomous Driving",
booktitle = "Proceedings of IEEE Workshop on Applications of Computer Vision",
month = "December",
year = "1992",
pages = "164 - 171",
url="http://www.ri.cmu.edu/pubs/pub_1031.html",
abstract="Describes a visual processing algorithm that supports autonomous road following. The algorithm requires that lane markings be present and attempts to track the lane markings on both lane boundaries. There are three stages of computation: extracting edges; matching extracted edge points with a geometric model of the road, and updating the geometric road model. All processing is confined to the 2-D image plane. No information about the motion of the vehicle is used. This algorithm has been implemented and tested using video taped road scenes. It performs robustly for both highways and rural roads. The algorithm runs at a sampling rate of 15 Hz and has a worst case latency of 139 milliseconds (ms). The algorithm is implemented under the NASA/NBS Standard Reference Model for Telerobotic Control System Architecture (NASREM) architecture and runs on a dedicated vision processing engine and a VME-based microprocessor system" 
}

@inproceedings{Schneiderman_1993_1033,
author = "Henry Schneiderman and M. Nashman and R. Lumia",
title = "Model-based Vision for Car Following",
booktitle = "Proceedings of SPIE Conference on Sensor Fusion",
month = "September",
year = "1993",
url ="http://www.ri.cmu.edu/pubs/pub_1033.html" 
}

@inproceedings{Schneiderman_1995_1030,
author = "Henry Schneiderman and M. Nashman and A. J. Wavering and R. Lumia",
title = "Vision-Based Robotic Convoy Driving",
booktitle = "Machine Vision and Applications",
year = "1995",
volume = "8",
number = "6",
pages = "359-364",
url="http://www.ri.cmu.edu/pubs/pub_1030.html" 
}

@inproceedings{Schneiderman_1994_1034,
author = "Henry Schneiderman and A. J. Wavering and M. Nashman and R. Lumia",
title = "Real-time Model-based Visual Tracking",
booktitle = "1994 International Workshop on Intelligent Robotic Systems",
year = "1994",
url="http://www.ri.cmu.edu/pubs/pub_1034.html" 
}

@inproceedings{Shum_1996_3605,
author = "Heung-Yeung Shum and Martial Hebert and Katsushi Ikeuchi",
title = "On 3-D shape similarity",
booktitle = "Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR '96)",
month = "June",
year = "1996",
pages = "526 - 531",
pdf="http://www.ri.cmu.edu/pub_files/pub2/shum_heung_yeung_1996_1/shum_heung_yeung_1996_1.pdf" 
}

@techreport{Shum_1995_1462,
author = "Heung-Yeung Shum and Martial Hebert and Katsushi Ikeuchi",
title = "On 3-D Shape Similarity",
institution = "Computer Science Department, Carnegie Mellon University",
year = "1995",
number = "CMU-CS-95-212",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub1/shum_heung_yeung_1995_2/shum_heung_yeung_1995_2.pdf" 
}

@techreport{Shum_1995_1463,
author = "Heung-Yeung Shum and Martial Hebert and Katsushi Ikeuchi",
title = "On 3-D Shape Synthetis",
institution = "Computer Science Department, Carnegie Mellon University",
year = "1995",
number = "CMU-CS-95-213",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub1/shum_heung_yeung_1995_3/shum_heung_yeung_1995_3.pdf" 
}

@techreport{Shum_1995_1457,
author = "Heung-Yeung Shum and Martial Hebert and Katsushi Ikeuchi and Raj Reddy",
title = "An Integral Approach To Free-Form Object Modeling",
institution = "Computer Science Department, Carnegie Mellon University",
month = "May",
year = "1995",
number = "CMU-CS-95-135",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub1/shum_heung_yeung_1995_1/shum_heung_yeung_1995_1.pdf" 
}

@inproceedings{Simmons_1995_1588,
author = "Reid Simmons and Eric Krotkov and L. Chrisman and Fabio Cozman and R. Goodwin and Martial Hebert and G. Heredia and S. Koenig and Pat Muir and Y. Shinoda and William Red L. Whittaker",
title = "Mixed-Mode Control of Navigation for a Lunar Rover",
booktitle = "Proceedings of the SSI/Princeton Space Manufacturing Conference",
year = "1995",
pdf="http://www.ri.cmu.edu/pub_files/pub1/simmons_reid_1995_3/simmons_reid_1995_3.pdf" 
}

@inproceedings{Simmons_1995_2650,
author = "Reid Simmons and Eric Krotkov and Lonnie Chrisman and Fabio Cozman and Richard Goodwin and Martial Hebert and Lalitesh Katragadda and Sven Koenig and G. Krishnaswamy and Y. Shinoda and William Red L. Whittaker and P. Klarer",
title = "Experience with Rover Navigation for Lunar-Like Terrains",
booktitle = "Proceedings of the 1995 Conference on Intelligent Robots and Systems (IROS '95)",
year = "1995",
pages = "441 - 446",
publisher = "IEEE",
pdf="http://www.ri.cmu.edu/pub_files/pub1/simmons_reid_1995_2/simmons_reid_1995_2.pdf",
abstract="Reliable navigation is critical for a lunar rover, both for autonomous traverses and safeguarded, remote teleoperation. This paper describes an implemented system that has autonomously driven a prototype wheeled lunar rover over a kilometer in natural, outdoor terrain. The navigation system uses stereo terrain maps to perform local obstacle avoidance, and arbitrates steering recommendations from both the user and the rover. The paper describes the system architecture, each of the major components, and the experimental results to date." 
}

@inproceedings{Simmons_1994_1435,
author = "Reid Simmons and Eric Krotkov and Martial Hebert and Lalitesh Katragadda",
title = "Experience with Rover Navigation for Lunar-Like Terrains",
booktitle = "International Lunar Exploration Conference",
month = "November",
year = "1994",
pdf="http://www.ri.cmu.edu/pub_files/pub1/simmons_reid_1994_1/simmons_reid_1994_1.pdf",
abstract="Reliable navigation is critical for a lunar rover, both for autonomous traverses and safeguarded, remote teleoperation. This paper describes an implemented system that has autonomously driven a prototype wheeled lunar rover over a kilometer in natural, outdoor terrain. The navigation system uses stereo terrain maps to perform local obstacle avoidance, and arbitrates steering recommendations from both the user and the rover. The paper describes the system architecture, each of the major components, and the experimental results to date." 
}

@inproceedings{Simmons_1996_674,
author = "Reid Simmons and Sebastian Thrun and Greg Armstrong and R. Goodwin and K. Haigh and S. Koenig and Shyjan Mahamud and Daniel Nikovski and Joseph O'Sullivan",
title = "Amelia",
booktitle = "Proceedings of the AAAI Thirteenth National Conference on Artificial Intelligence",
year = "1996",
url="http://www.ri.cmu.edu/pubs/pub_674.html" 
}

@article{Simon_1995_1179,
author = "David Simon and Martial Hebert and Takeo Kanade",
title = "Techniques For Fast And Accurate Intrasurgical Registration",
journal = "Journal of Image Guided Surgery",
year = "1995",
volume = "1",
number = "1",
pages = "17-29",
pdf="http://www.ri.cmu.edu/pub_files/pub2/simon_david_1995_1/simon_david_1995_1.pdf",
abstract="The goal of intra-surgical registration is to establish a common reference frame between pre-surgical and intra-surgical 3-D data sets that correspond to the same anatomy. This paper presents two novel techniques which have application to this problem: high-speed pose tracking, and intra-surgical data selection. In the first part of this paper, we describe an approach for tracking the pose of arbitrarily-shaped rigid objects at rates up to 10Hz. Static accuracies on the order of 1mm in translation and 1 degree in rotation have been achieved. We have demonstrated the technique on a human face using a high-speed VLSI range sensor; however, the technique is independent of the sensor used or the anatomy tracked. In the second part of this paper, we describe a general purpose approach for selecting near-optimal, intra-surgical registration data. Due to high costs associated with the acquisition of intra-surgical data, it is desirable to minimize the amount of data acquired, while ensuring that registration accuracy requirements are met. We synthesize near-optimal intra-surgical data sets, based upon an analysis of differential surface properties of pre-surgical data. We demonstrate, using data from a human femur, that discrete point data sets selected using our method provide superior pose refinement accuracy to those selected by human experts." 
}

@inproceedings{Simon_1994_1178,
author = "David Simon and Martial Hebert and Takeo Kanade",
title = "Real-time 3-D pose estimation using a high-speed range sensor",
booktitle = "Proceedings of IEEE International Conference on Robotics and Automation (ICRA '94)",
month = "May",
year = "1994",
volume = "3",
pages = "2235-2241",
pdf="http://www.ri.cmu.edu/pub_files/pub2/simon_david_1994_1/simon_david_1994_1.pdf",
abstract="This paper describes a system which can perform full 3-D pose estimation of a single arbitrarily shaped, rigid object at rates up to 10 Hz. A triangular mesh model of the object to be tracked is generated offline using conventional range sensors. Real-time range data of the object is sensed by the CMU high speed VLSI range sensor. Pose estimation is performed by registering the real-time range data to the triangular mesh model using an enhanced implementation of the Iterative Closest Point (ICP) Algorithm introduced by Besl and McKay (1992). The method does not require explicit feature extraction or specification of correspondence. Pose estimation accuracies of the order of 1 percent of the object size in translation, and 1 degree in rotation have been measured." 
}

@inproceedings{Simon_1994_1734,
author = "David Simon and Martial Hebert and Takeo Kanade",
title = "Techniques for Fast and Accurate Intra-Surgical Registration",
booktitle = "First International Symposium on Medical Robotics and Computer Assisted Surgery",
month = "September",
year = "1994",
pages = "90-97" 
}

@techreport{Simon_1993_313,
author = "David Simon and Martial Hebert and Takeo Kanade",
title = "Real-Time 3-D Pose Estimation Using a High-Speed Range Sensor",
institution = "Robotics Institute, Carnegie Mellon University",
month = "November",
year = "1993",
number = "CMU-RI-TR-93-24",
address = "Pittsburgh, PA",
abstract="This report describes a system which can perform full 3-D pose estimation of a single arbitrarily shaped, rigid object at rates up to 10Hz. A triangular mesh model of the object to be tracked is generated offline using conventional range sensors. Real-time range data of the object is sensed by the CMU high speed VLSI range sensor. Pose estimation is performed by registering the real-time range data to the triangular mesh model using an enhanced implementation of the Iterative Closest Point (ICP) Algorithm introduced by Besl and McKay. The method does not require explicit feature extraction or specification of correspondence. Pose estimation accuracies on the order to 1mm in translation and 1 degree in rotation have been measured.",
pdf=" http://www.ri.cmu.edu/pub_files/pub1/simon_david_1993_1/simon_david_1993_1.pdf" 
}

@inproceedings{Stentz_1995_2671,
author = "Anthony (Tony) Stentz and Martial Hebert",
title = "A Complete Navigation System for Goal Acquisition in Unknown Environments",
booktitle = "Proceedings 1995 IEEE/RSJ International Conference On Intelligent Robotic Systems (IROS '95)",
month = "August",
year = "1995",
volume = "1",
pages = "425 - 432",
pdf="http://www.ri.cmu.edu/pub_files/pub1/stentz_anthony__tony__1995_2/stentz_anthony__tony__1995_2.pdf",
abstract="Most autonomous outdoor navigation systems tested on actual robots have centered on local navigation tasks such as avoiding obstacles or following roads. Global navigation has been limited to simple wandering, path tracking, straight-line goal seeking behaviors, or executing a sequence of scripted local behaviors. These capabilities are insufficient for unstructured and unknown environments, where replanning may be needed to account for new information discovered in every sensor image. To address these problems, the authors developed a complete system that integrates local and global navigation. The local system uses a scanning laser rangefinder to detect and avoid obstacles. The global system uses an incremental path planning algorithm to optimally replan the global path for each detected obstacle. A control arbiter steers the robot to achieve the proper balance between safety and goal acquisition. This system was tested on a real robot and successfully drove it 1.4 kilometers to find a goal given no a priori map of the environment. " 
}

@techreport{Stentz_1994_327,
author = "Anthony (Tony) Stentz and Martial Hebert",
title = "A Complete Navigation System for Goal Acquisition in Unknown Environments",
institution = "Robotics Institute, Carnegie Mellon University",
month = "April",
year = "1994",
number = "CMU-RI-TR-94-07",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub3/stentz_anthony__tony__1994_1/stentz_anthony__tony__1994_1.pdf",
abstract="Autonomous outdoor navigation has broad application in mining, construction, planetary exploration, and military reconnaissance. To date, most of the work tested on actual robots has centered on local navigation tasks such as avoiding obstacles or following roads. Global navigation has been limited to simple wandering, path tracking, straight-line goal seeking behaviors, or executing a sequence of scripted local behaviors. The problem of global navigation in outdoor environments has been addressed in the literature, but it is generally assumed that the world exhibits coarse topological structure, most of which is known, and that sensors and position estimation systems provide highly-accurate data. These assumptions break down for real robots in highly unstructured and unknown environments. With every image, the sensors provide new information about the world that can impact the robot's path to the goal. Some of the information is real, some arises from noise, and some arises from aliasing due to robot position error. Replanning may be needed for every image, and it may be nontrivial due to the unstructured nature of the environment. To address these problems, we have developed a complete system that integrates local and global navigation. This system is capable of finding goal given no a priori map of the environment. It is robust to noise, vehicle position error, and is able to replan in real-time. We describe the system and present the results of experiments performed using a real robot." 
}

@inproceedings{Thorpe_1991_1094,
author = "Charles Thorpe and Omead Amidi and Jay Gowdy and Martial Hebert and D. Pomerleau.",
title = "Integrating Position Measurement and Image Understanding for Autonomous Vehicle Navigation",
booktitle = "Proceedings of 2nd International Workshop on High Precision Navigation",
month = "November",
year = "1991" 
}

@inproceedings{Thorpe_1993_612,
author = "Charles Thorpe and R. Craig Coulter and Martial Hebert and Todd Jochem and Dirk Langer and Dean Pomerleau and Julio Rosenblatt and W. Ross and Anthony (Tony) Stentz",
title = "Smart Cars: The CMU Navlab",
booktitle = "Proceedings of WORLD MED93",
month = "October",
year = "1993" 
}

@inproceedings{Thorpe_1996_1655,
author = "Charles Thorpe and Martial Hebert",
title = "Mobile Robotics: Perspectives and Realities",
booktitle = "proceedings of International Workshop on Advanced Robotics and Intelligent Machines",
month = "April",
year = "1996",
note = "Keynote addresses" 
}

@incollection{Thorpe_1992_1609,
author = "Charles Thorpe and Martial Hebert and Takeo Kanade and Steven Shafer",
editor = "Ichiro Masaki",
title = "The New Generation System for the CMU Navlab",
booktitle = "Vision-Based Vehicle Guidance",
publisher = "Springer-Verlag",
year = "1992",
note = "A different version of this paper appears as the journal paper, in two parts, "Towards Autonomous Driving: The CMU Navlab"" 
}

@article{Thorpe_1991_1622,
author = "Charles Thorpe and Martial Hebert and Takeo Kanade and Steven Shafer",
title = "Toward Autonomous Driving: The CMU Navlab. Part I: Perception",
journal = "IEEE Expert",
month = "August",
year = "1991",
volume = "6",
number = "4",
pages = "31 - 42",
pdf="http://www.ri.cmu.edu/pub_files/pub2/thorpe_charles_1991_2/thorpe_charles_1991_2.pdf",
abstract="The Navlab project, which seeks to build an autonomous robot that can operate in a realistic environment with bad weather, bad lighting, and bad or changing roads, is discussed. The perception techniques developed for the Navlab include road-following techniques using color classification and neural nets. These are discussed with reference to three road-following systems, SCARF, YARF, and ALVINN. Three-dimensional perception using three types of terrain representation (obstacle maps, terrain feature maps, and high-resolution maps) is examined. It is noted that perception continues to be an obstacle in developing autonomous vehicles. This work is part of the Defense Advanced Research Project Agency. Strategic Computing Initiative." 
}

@article{Thorpe_1991_1623,
author = "Charles Thorpe and Martial Hebert and Takeo Kanade and Steven Shafer",
title = "Toward Autonomous Driving: The CMU Navlab. Part II: System and Architecture",
journal = "IEEE Expert",
month = "August",
year = "1991",
volume = "6",
number = "4",
pages = "44 - 52",
pdf="http://www.ri.cmu.edu/pub_files/pub2/thorpe_charles_1991_1/thorpe_charles_1991_1.pdf",
abstract="A description is given of EDDIE, the architecture for the Navlab mobile robot which provides a toolkit for building specific systems quickly and easily. Included in the discussion are the annotated maps used by EDDIE and the Navlab's road-following system, called the Autonomous Mail Vehicle, which was built using EDDIE and its annotated maps as a basis. The contributions of the Navlab project and the lessons learned from it are examined. " 
}

@article{Thorpe_1988_1624,
author = "Charles Thorpe and Martial Hebert and Takeo Kanade and Steven Shafer",
title = "Vision and navigation for the Carnegie-Mellon Navlab",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
month = "May",
year = "1988",
volume = "10",
number = "3",
pages = "362 - 373",
note = "Other versions appeared in "High Precision Navigation" (Springer-Verlag, 1989) and in "Annual Reviews of Computer Science", Volume 2, 1987." pdf="http://www.ri.cmu.edu/pub_files/pub2/thorpe_charles_1988_1/thorpe_charles_1988_1.pdf" 
}

@incollection{Thorpe_1987_2392,
author = "Charles Thorpe and Martial Hebert and Takeo Kanade and Steven Shafer",
editor = "J. Traub, et. al",
title = "Vision and Navigation for Carnegie Mellon Navlab",
booktitle = "Annual Review of Computer Science",
pages = "521-556",
publisher = "Annual Reviews Inc., CA",
year = "1987",
volume = "2" 
}

@techreport{Zhang_1996_431,
author = "Dongmei Zhang and Martial Hebert",
title = "Multi-Scale Classification of 3-D Objects",
institution = "Robotics Institute, Carnegie Mellon University",
month = "November",
year = "1996",
number = "CMU-RI-TR-96-39",
address = "Pittsburgh, PA",
pdf="http://www.ri.cmu.edu/pub_files/pub1/zhang_dongmei_1996_1/zhang_dongmei_1996_1.pdf" 
}