Cover image for 3D-position tracking and control for all-terrain robots
Title:
3D-position tracking and control for all-terrain robots
Personal Author:
Series:
Springer tracts in advanced robotics, v. 43
Publication Information:
Berlin, GW : Springer, 2008
Physical Description:
xvi, 103 p. : ill. ; 25 cm.
ISBN:
9783540782865

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Library
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Call Number
Material Type
Item Category 1
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30000010195495 TJ211.415 L36 2008 Open Access Book Book
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33000000010062 TJ211.415 L36 2008 Open Access Book Book
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Summary

Summary

Rough terrain robotics is a fast evolving field of research and a lot of effort is deployed towards enabling a greater level of autonomy for outdoor vehicles. This book demonstrates how the accuracy of 3D position tracking can be improved by considering rover locomotion in rough terrain as a holistic problem. Although the selection of appropriate sensors is crucial to accurately track the rover's position, it is not the only aspect to consider. Indeed, the use of an unadapted locomotion concept severely affects the signal to noise ratio of the sensors, which leads to poor motion estimates. In this work, a mechanical structure allowing smooth motion across obstacles with limited wheel slip is used. In particular, it enables the use of odometry and inertial sensors to improve the position estimation in rough terrain. A method for computing 3D motion increments based on the wheel encoders and chassis state sensors is developed. Because it accounts for the kinematics of the rover, this method provides better results than the standard approach. To further improve the accuracy of the position tracking and the rover's climbing performance, a controller minimizing wheel slip is developed. The algorithm runs online and can be adapted to any kind of passive wheeled rover. Finally, sensor fusion using 3D-Odometry, inertial sensors and visual motion estimation based on stereovision is presented. The experimental results demonstrate how each sensor contributes to increase the accuracy and robustness of the 3D position estimation.


Table of Contents

1 Introductionp. 1
1.1 Autonomy in Rough Terrainp. 1
1.2 The Open Challenges of Rough Terrain Navigationp. 2
1.2.1 Lack of Prior Informationp. 2
1.2.2 Perceptionp. 2
1.2.3 Locomotionp. 2
1.3 Research Context and Scopep. 3
1.4 Structure of the Bookp. 4
2 The SOLERO Roverp. 7
2.1 Mechanical Design of SOLEROp. 7
2.2 Control Architecturep. 11
2.2.1 Sensors and Actuatorsp. 11
2.2.2 Software Architecturep. 17
2.3 Summaryp. 19
3 3D-Odometryp. 21
3.1 3D-Odometryp. 21
3.1.1 Bogie Displacementp. 22
3.1.2 3D Displacementp. 25
3.1.3 Contact Angles Estimationp. 27
3.2 Experimental Resultsp. 27
3.3 Summaryp. 32
4 Control in Rough-Terrainp. 33
4.1 Quasi-static Model of a Wheeled Roverp. 34
4.1.1 Mobility Analysisp. 34
4.1.2 A 3D Static Modelp. 36
4.2 Torque Optimizationp. 36
4.2.1 Wheel Slip Modelp. 37
4.2.2 Optimization Algorithmp. 38
4.2.3 Torque Optimization for SOLEROp. 41
4.3 Rover Motionp. 43
4.4 Experimental Resultsp. 45
4.4.1 Simulation Toolsp. 45
4.4.2 Experimentsp. 46
4.5 Wheel-Ground Contact Anglesp. 49
4.6 Summaryp. 50
5 Position Tracking in Rough-Terrainp. 53
5.1 Sensor Selection for Motion Perceptionp. 53
5.2 Uncertainties Propagationp. 56
5.2.1 Coordinate Systems and Transformationsp. 56
5.2.2 Error Propagationp. 57
5.3 Sensor Fusionp. 58
5.3.1 Sensor Modelsp. 60
5.3.2 State Prediction Modelp. 63
5.4 Experimental Resultsp. 65
5.4.1 Inertial Sensor and 3D-Odometryp. 65
5.4.2 Enhancement with VMEp. 73
5.5 Summaryp. 78
6 Conclusionp. 81
A Kinematic and Quasi-static Model of SOLEROp. 83
A.1 Kinematic Modelp. 83
A.1.1 The Bogiesp. 84
A.1.2 The Main Bodyp. 85
A.1.3 The Front Forkp. 85
A.2 The Quasi-static Model of SOLEROp. 86
A.2.1 Linear Dependence of the Wheel Torquesp. 89
A.2.2 Equal Torque Solutionp. 90
B Linearized Modelsp. 91
B.1 Accelerometers Modelp. 91
B.2 Gyroscopes State Transitionp. 92
C The Gauss-Markov Processp. 93
D Visual Motion Estimationp. 97
Referencesp. 99
Indexp. 105