Coordinating multiple mobile robots for obstacle avoidance using cloud computing

• Published in: Asian Journal of Control
• Main Authors: Song, Kai‐Tai, Sun, Yu‐Xuan
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2020
• Subjects: Orca
• Online Access: http://dx.doi.org/10.1002/asjc.2431; https://onlinelibrary.wiley.com/doi/pdf/10.1002/asjc.2431; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/asjc.2431

Abstract This study presents a motion planning method for coordinating multiple mobile robots for collision‐free navigation. A control architecture that uses cloud computing is proposed for the acquisition of real‐time robotic data and to coordinate multiple robots in an unstructured environment. The system consists of collision‐free path planning for multiple robots, obstacle avoidance, and navigation control. The path planning method was developed based on the optimal reciprocal collision avoidance (ORCA) algorithm to generate a velocity set of each robot in the system. A laser scanner is used to detect obstacles for each robot. Appropriate obstacle avoidance behaviors are generated using sensory information. A behavior‐fusion control scheme combines obstacle avoidance and collision‐free path planning to coordinate multiple robots. The proposed anti‐collision motion planning method for multiple robots prevents collisions with unexpected obstacles and with other robots in the environment. The experimental results show that multiple mobile robots can navigate to targets that are assigned by the cloud server without colliding with other robots, regardless of whether there are unexpected static or dynamic obstacles in the environment.