TY - GEN
T1 - Vision-based estimation of slip angle for mobile robots and planetary rovers
AU - Reina, Giulio
AU - Ishigami, Genya
AU - Nagatani, Keiji
AU - Yoshida, Kazuya
PY - 2008
Y1 - 2008
N2 - For a mobile robot it is critical to detect and compensate for slippage, especially when driving in rough terrain environments. Due to its highly unpredictable nature, drift largely affects the accuracy of localization and control systems, even leading, in extreme cases, to the danger of vehicle entrapment with consequent mission failure. This paper presents a novel method for lateral slip estimation based on visually observing the trace produced by the wheels of the robot, during traverse of soft, deformable terrain, as that expected for lunar and planetary rovers. The proposed algorithm uses a robust Hough transform enhanced by fuzzy reasoning to estimate the angle of inclination of the wheel trace with respect to the vehicle reference frame. Any deviation of the wheel trace from the planned path of the robot suggests occurrence of sideslip that can be detected, and more interestingly, measured. This allows one to estimate the actual heading angle of the robot, usually referred to as the slip angle. The details of the various steps of the visual algorithm are presented and the results of experimental tests performed in the field with an allterrain rover are shown, proving the method to be effective and robust.
AB - For a mobile robot it is critical to detect and compensate for slippage, especially when driving in rough terrain environments. Due to its highly unpredictable nature, drift largely affects the accuracy of localization and control systems, even leading, in extreme cases, to the danger of vehicle entrapment with consequent mission failure. This paper presents a novel method for lateral slip estimation based on visually observing the trace produced by the wheels of the robot, during traverse of soft, deformable terrain, as that expected for lunar and planetary rovers. The proposed algorithm uses a robust Hough transform enhanced by fuzzy reasoning to estimate the angle of inclination of the wheel trace with respect to the vehicle reference frame. Any deviation of the wheel trace from the planned path of the robot suggests occurrence of sideslip that can be detected, and more interestingly, measured. This allows one to estimate the actual heading angle of the robot, usually referred to as the slip angle. The details of the various steps of the visual algorithm are presented and the results of experimental tests performed in the field with an allterrain rover are shown, proving the method to be effective and robust.
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U2 - 10.1109/ROBOT.2008.4543254
DO - 10.1109/ROBOT.2008.4543254
M3 - Conference contribution
AN - SCOPUS:51649088441
SN - 9781424416479
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 486
EP - 491
BT - 2008 IEEE International Conference on Robotics and Automation, ICRA 2008
T2 - 2008 IEEE International Conference on Robotics and Automation, ICRA 2008
Y2 - 19 May 2008 through 23 May 2008
ER -