Coordinating multiple mobile robots for obstacle avoidance using cloud computing

Kai-Tai Song*, Yu Xuan Sun

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

Original languageEnglish
JournalAsian Journal of Control
StateAccepted/In press - 2020


  • cloud computing
  • mobile robots
  • multiple robots
  • obstacle avoidance

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