A multirange architecture for collision‐free off‐road robot navigation

We present a multilayered mapping, planning, and command execution system developed and tested on the LAGR mobile robot. Key to robust performance under uncertainty is the combination of a short‐range perception system operating at high frame rate and low resolution and a long‐range, adaptive vision system operating at lower frame rate and higher resolution. The short‐range module performs local planning and obstacle avoidance with fast reaction times, whereas the long‐range module performs strategic visual planning. Probabilistic traversability labels provided by the perception modules are combined and accumulated into a robot‐centered hyperbolic‐polar map with a 200‐m effective range. Instead of using a dynamical model of the robot for short‐range planning, the system uses a large lookup table of physically possible trajectory segments recorded on the robot in a wide variety of driving conditions. Localization is performed using a combination of global positioning system, wheel odometry, inertial measurement unit, and a high‐speed, low‐complexity rotational visual odometry module. The end‐to‐end system was developed and tested on the LAGR mobile robot and was verified in independent government tests. © 2008 Wiley Periodicals, Inc.

[1]  J. Meditch,et al.  Applied optimal control , 1972, IEEE Transactions on Automatic Control.

[2]  J. Baird,et al.  The locus of environmental attention , 1981 .

[3]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[4]  Yutaka Kanayama,et al.  Trajectory generation for mobile robots , 1984 .

[5]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[6]  Susumu Tachi,et al.  A method of autonomous locomotion for mobile robots , 1986, Adv. Robotics.

[7]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[8]  Yutaka Kanayama,et al.  Smooth local path planning for autonomous vehicles , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[9]  D.J. Kriegman,et al.  Stereo vision and navigation in buildings for mobile robots , 1989, IEEE Trans. Robotics Autom..

[10]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[11]  G. Oriolo,et al.  Fuzzy Maps: A New Tool for Mobile Robot Perception and Planning , 1997 .

[12]  Marilena Vendittelli,et al.  Fuzzy maps: A new tool for mobile robot perception and planning , 1997, J. Field Robotics.

[13]  Alonzo Kelly,et al.  Stereo Vision Enhancements for Low-Cost Outdoor Autonomous Vehicles , 1998 .

[14]  A Hybrid Human-Computer Autonomous Vehicle Architecture , 1998 .

[15]  Hugh F. Durrant-Whyte,et al.  A high integrity IMU/GPS navigation loop for autonomous land vehicle applications , 1999, IEEE Trans. Robotics Autom..

[16]  Bill Triggs,et al.  Camera pose and calibration from 4 or 5 known 3D points , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[17]  Andrew Zisserman,et al.  A Six Point Solution for Structure and Motion , 2000, ECCV.

[18]  Karl Murphy,et al.  Driving autonomously off-road up to 35 km/h , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[19]  Eric Feron,et al.  Aggressive Maneuvering of Autonomous Aerial Vehicles: A Human-Centered Approach , 2000 .

[20]  Larry Matthies,et al.  Stereo vision and rover navigation software for planetary exploration , 2002, Proceedings, IEEE Aerospace Conference.

[21]  Alison K. Brown,et al.  Inertial Navigation Electro-Optical Aiding During GPS Dropouts , 2002 .

[22]  James P. Ostrowski,et al.  Visual motion planning for mobile robots , 2002, IEEE Trans. Robotics Autom..

[23]  Kian Hsiang Low,et al.  Integrated planning and control of mobile robot with self-organizing neural network , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[24]  G. Ulivi,et al.  Indoor robot navigation using log-polar local maps , 2003 .

[25]  Alonzo Kelly,et al.  Reactive Nonholonomic Trajectory Generation via Parametric Optimal Control , 2003, Int. J. Robotics Res..

[26]  Sebastian Thrun,et al.  Robotic mapping: a survey , 2003 .

[27]  Sven Behnke,et al.  Local Multiresolution Path Planning , 2003, RoboCup.

[28]  James R. Bergen,et al.  Visual odometry , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[29]  E. Stewart,et al.  Intel Integrated Performance Primitives: How to Optimize Software Applications Using Intel IPP , 2004 .

[30]  Michael Beetz.  Structured Reactive Controllers , 2004, Autonomous Agents and Multi-Agent Systems.

[31]  Eric Deeson,et al.  Online learning , 2005, Br. J. Educ. Technol..

[32]  Munther A. Dahleh,et al.  Maneuver-based motion planning for nonlinear systems with symmetries , 2005, IEEE Transactions on Robotics.

[33]  Frederik Schaffalitzky,et al.  A minimal solution for relative pose with unknown focal length , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[34]  Frederik Schaffalitzky,et al.  How hard is 3-view triangulation really? , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[35]  Alonzo Kelly,et al.  TERRAIN-ADAPTIVE GENERATION OF OPTIMAL CONTINUOUS TRAJECTORIES FOR MOBILE ROBOTS , 2005 .

[36]  Roberto Manduchi,et al.  Obstacle Detection and Terrain Classification for Autonomous Off-Road Navigation , 2005, Auton. Robots.

[37]  Alonzo Kelly,et al.  Toward Reliable Off Road Autonomous Vehicles Operating in Challenging Environments , 2006, Int. J. Robotics Res..

[38]  Andrew J. Davison,et al.  A visual compass based on SLAM , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[39]  James S. Albus,et al.  Learning in a hierarchical control system: 4D/RCS in the DARPA LAGR program , 2006, J. Field Robotics.

[40]  Sebastian Thrun,et al.  A Self-Supervised Terrain Roughness Estimator for Off-Road Autonomous Driving , 2006, UAI.

[41]  M. Veth,et al.  Stochastic constraints for efficient image correspondence search , 2006, IEEE Transactions on Aerospace and Electronic Systems.

[42]  Pietro Perona,et al.  Slip Prediction Using Visual Information , 2006, Robotics: Science and Systems.

[43]  Steven Dubowsky,et al.  Hazard avoidance for high‐speed mobile robots in rough terrain , 2006, J. Field Robotics.

[44]  J. Borenstein,et al.  Current-Based Slippage Detection and Odometry Correction for Mobile Robots and Planetary Rovers , 2006, IEEE Transactions on Robotics.

[45]  J. Andrew Bagnell,et al.  Improving robot navigation through self‐supervised online learning , 2006, J. Field Robotics.

[46]  Larry Matthies,et al.  Two years of Visual Odometry on the Mars Exploration Rovers: Field Reports , 2007 .

[47]  Michael Happold,et al.  A Bayesian approach to imitation learning for robot navigation , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[48]  Urs A. Muller,et al.  SPEED-RANGE DILEMMAS FOR VISION-BASED NAVIGATION IN UNSTRUCTURED TERRAIN , 2007 .

[49]  K. Konolige.  Rough Terrain Visual Odometry , 2007 .

[50]  Ashutosh Saxena,et al.  Depth Estimation Using Monocular and Stereo Cues , 2007, IJCAI.

[51]  Karsten Berns,et al.  Real-Time Visual Self-Localisation in Dynamic Environments , 2007, AMS.

[52]  Larry H. Matthies,et al.  Two years of Visual Odometry on the Mars Exploration Rovers , 2007, J. Field Robotics.

[53]  Yann LeCun,et al.  Online Learning for Offroad Robots: Spatial Label Propagation to Learn Long-Range Traversability , 2007, Robotics: Science and Systems.

[54]  Ian D. Reid,et al.  Mapping Large Loops with a Single Hand-Held Camera , 2007, Robotics: Science and Systems.

[55]  Karl Iagnemma,et al.  Model-Based Wheel Slip Detection for Outdoor Mobile Robots , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[56]  Clark N. Taylor,et al.  Improving MAV pose estimation using visual information , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[57]  Karl Iagnemma,et al.  Classification-Based Wheel Slip Detection and Detector Fusion for Outdoor Mobile Robots , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[58]  Gregory Z. Grudic,et al.  Online Learning of Multiple Perceptual Models for Navigation in Unknown Terrain , 2007, FSR.

[59]  Michael Veth,et al.  Two-Dimensional Stochastic Projections for Tight Integration of Optical and Inertial Sensors for Navigation , 2007 .

[60]  S. Thrun,et al.  Optical Flow Approaches for Self-supervised Learning in Autonomous Mobile Robot Navigation , 2007 .

[61]  Ian D. Reid,et al.  Simultaneous Localisation and Mapping in Dynamic Environments (SLAMIDE) with Reversible Data Associa , 2007, Robotics: Science and Systems.

[62]  Pietro Perona,et al.  Fast Terrain Classification Using Variable-Length Representation for Autonomous Navigation , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[63]  Larry H. Matthies,et al.  Learning long-range terrain classification for autonomous navigation , 2008, 2008 IEEE International Conference on Robotics and Automation.

[64]  Kurt Konolige,et al.  Fast color/texture segmentation for outdoor robots , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[65]  Wolfram Burgard,et al.  Simultaneous Localisation and Mapping in Dynamic Environments (SLAMIDE) with Reversible Data Association , 2008 .

[66]  Ben Taskar,et al.  Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields , 2008, 2008 IEEE International Conference on Robotics and Automation.

[67]  C. Stachniss,et al.  Online Learning for Offroad Robots: Using Spatial Label Propagation to Learn Long-Range Traversability , 2008 .

[68]  Yann LeCun,et al.  Learning long‐range vision for autonomous off‐road driving , 2009, J. Field Robotics.