Mobile Robot Navigation in Cluttered Environment using Reactive Elliptic Trajectories

Reactive navigation in very cluttered environment while insuring maximum safety and task efficiency is a challenging subject. This paper proposes online and adaptive elliptic trajectories to perform smooth and safe mobile robot navigation. These trajectories use limit-cycle principle already applied in the literature but with the difference that the applied limit-cycles are now elliptic (not circular) and are more generic and flexible to perform navigation in environments with different kinds of obstacles shape. The set points given to the robot are generated while following reactive obstacle avoidance algorithm embedded in a multi-controller architecture (Obstacle avoidance and Attraction to the target controllers). This algorithm uses specific reference frame which gives accurate indication of robot situation. The robot knows thus if it must avoid the obstacle in clockwise or counterclockwise direction and prevent robot from local minima, dead ends and oscillations. The stability of the proposed bottom-up control architecture is proved according to Lyapunov synthesis. Simulations and experiments in different environments are performed to demonstrate the efficiency and the reliability of the proposed control architecture.

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

[2]  Lounis Adouane,et al.  Behavioral and distributed architecture of control for minimalist mobile robots , 2006 .

[3]  O. Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[4]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[5]  René Zapata,et al.  DVZ-Based Collision Avoidance Control of Non-Holonomic Mobile Manipulators , 2004 .

[6]  Jong-Hwan Kim,et al.  A real-time limit-cycle navigation method for fast mobile robots and its application to robot soccer , 2003, Robotics Auton. Syst..

[7]  Christian Laugier,et al.  The CyCab: a car-like robot navigating autonomously and safely among pedestrians , 2005, Robotics Auton. Syst..

[8]  Xiaoming Hu,et al.  A hybrid control approach to action coordination for mobile robots , 1999, Autom..

[9]  Min Seok Jie,et al.  Real Time Obstacle Avoidance for Mobile Robot Using Limit-Cycle and Vector Field Method , 2006, KES.

[10]  Brett R. Fajen,et al.  Visual navigation and obstacle avoidance using a steering potential function , 2006, Robotics Auton. Syst..

[11]  Lounis Adouane Hybrid and Safe Control Architecture for Mobile Robot Navigation , 2009 .

[12]  Igor Boiko Frequency-Domain Analysis of Relay Feedback Systems , 2011 .

[13]  Daniel E. Koditschek,et al.  Exact robot navigation using artificial potential functions , 1992, IEEE Trans. Robotics Autom..

[14]  Thierry Fraichard,et al.  Trajectory planning in a dynamic workspace: a 'state-time space' approach , 1998, Adv. Robotics.

[15]  Jean-Claude Latombe,et al.  Robot motion planning , 1970, The Kluwer international series in engineering and computer science.

[16]  Mark H. Overmars,et al.  Roadmap-based motion planning in dynamic environments , 2005, IEEE Trans. Robotics.

[17]  Simon X. Yang,et al.  A Hybrid Robot Navigation Approach Based on Partial Planning and Emotion-Based Behavior Coordination , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Ronald C. Arkin,et al.  Motor Schema — Based Mobile Robot Navigation , 1989, Int. J. Robotics Res..

[19]  Ricardo O. Carelli,et al.  Switching Control of Mobile Robots for Autonomous Navigation in Unknown Environments , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[20]  W. Gander,et al.  Fitting of circles and ellipses: Least squares solution , 1994 .

[21]  Lounis Adouane,et al.  Orbital Obstacle Avoidance Algorithm for Reliable and On-Line Mobile Robot Navigation , 2009 .