Laser-Based Obstacle Avoidance and Road Quality Detection for Autonomous Bicycles

This paper presents a novel design and implementation approach for a laser range sensor (LRS)-based obstacle avoidance and road quality detection system specifically created to be used onboard an autonomous bicycle. The system uses the measurements from a single LSR to detect dynamic obstacles inside the bicycle’s environment and avoid the ones whose paths intersect with its own. The LSR’s mechanical base and rotating mechanism were specially designed to fit the lightweight structure of the bicycle and a specific rotation pattern on the bicycle’s sagittal plane was created to maximize sensing efficiency. The RANSAC Line Detection algorithm is applied to detect the ground line, assess the road surface quality, and avoid bumps or holes on the bicycle path. Our experimental results show promising bicycle behavior and reliable obstacle avoidance at different speeds.

[1]  Jerrold E. Marsden,et al.  Control for an autonomous bicycle , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[2]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[3]  Naresh K. Sinha,et al.  Modern Control Systems , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[4]  Reinhard Klein,et al.  Efficient RANSAC for Point‐Cloud Shape Detection , 2007, Comput. Graph. Forum.

[5]  Y. Yavin,et al.  Stabilization and control of the motion of an autonomous bicycle by using a rotor for the tilting moment , 1999 .

[6]  L. Keo,et al.  Trajectory control for an autonomous bicycle with balancer , 2008, 2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

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

[8]  Himanshu Dutt Sharma,et al.  A Robotic Model (ROBI) of Autonomous Bicycle System , 2006, 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06).

[9]  Andrea Cherubini,et al.  Visual navigation of a mobile robot with laser-based collision avoidance , 2013, Int. J. Robotics Res..

[10]  Yoram Koren,et al.  Real-time obstacle avoidance for fact mobile robots , 1989, IEEE Trans. Syst. Man Cybern..

[11]  Monson H. Hayes,et al.  Robust lane detection and tracking with ransac and Kalman filter , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).