A New Conflict Resolution Method for Multiple Mobile Robots in Cluttered Environments With Motion-Liveness

• Published in: IEEE transactions on cybernetics Vol. 48; no. 1; pp. 300 - 311
• Main Authors: Shahriari, Mohammadali, Biglarbegian, Mohammad
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Clustering; Collision avoidance; Computational efficiency; Computer simulation; Conflict resolution; Intersections; meta-heuristic optimization; Mobile robots; motion-liveness; multiple mobile robots (MMRs); Optimization; Parallel programming; Path planning; Real-time systems; Robot dynamics; Robot kinematics; Robots; System recovery; Travel time
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2016.2633331

This paper presents a new conflict resolution methodology for multiple mobile robots while ensuring their motion-liveness, especially for cluttered and dynamic environments. Our method constructs a mathematical formulation in a form of an optimization problem by minimizing the overall travel times of the robots subject to resolving all the conflicts in their motion. This optimization problem can be easily solved through coordinating only the robots' speeds. To overcome the computational cost in executing the algorithm for very cluttered environments, we develop an innovative method through clustering the environment into independent subproblems that can be solved using parallel programming techniques. We demonstrate the scalability of our approach through performing extensive simulations. Simulation results showed that our proposed method is capable of resolving the conflicts of 100 robots in less than 1.23 s in a cluttered environment that has 4357 intersections in the paths of the robots. We also developed an experimental testbed and demonstrated that our approach can be implemented in real time. We finally compared our approach with other existing methods in the literature both quantitatively and qualitatively. This comparison shows while our approach is mathematically sound, it is more computationally efficient, scalable for very large number of robots, and guarantees the live and smooth motion of robots.