Decentralized Multi-Robot Collision Avoidance: A Systematic Review from 2015 to 2021

• Published in: Symmetry
• Main Authors: Mehak Raibail, Abdul Hadi Abd Rahman, Ghassan Jasim AL-Anizy, Mohammad Faidzul Nasrudin, Mohd Shahrul Mohd Nadzir, Nor Mohd Razif Noraini, Tan Siok Yee
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2022
• Subjects: decentralized; multi-robot; collision avoidance; path planning; Mathematics; QA1-939; Orca
• Online Access: https://doi.org/10.3390/sym14030610; https://doaj.org/article/1e10113272ef4ba69e9cc33b8e57862c

An exploration task can be performed by a team of mobile robots more efficiently than human counterparts. They can access and give live updates for hard-to-reach areas such as a disaster site or a sewer. However, they face some issues hindering them from optimal path planning due to the symmetrical shape of the environments. Multiple robots are expected to explore more areas in less time while solving robot localization and collision-avoidance issues. When deploying a multi-robot system, it is ensured that the hardware parts do not collide with each other or the surroundings, especially in symmetric environments. Two types of methods are used for collision avoidance: centralized and decentralized. The decentralized approach has mainly been used in recent times, as it is computationally less expensive. This article aims to conduct a systematic literature review of different collision-avoidance strategies and analyze the performance of innovative collision-avoidance techniques. Different methods such as Reinforcement Learning (RL), Model Predictive Control (MPC), Altruistic Coordination, and other approaches followed by selected studies are also discussed. A total of 17 studies are included in this review, extracted from seven databases. Two experimental designs are studied: empty/open space and confined indoor space. Our analysis observed that most of the studies focused on empty/open space scenarios and verified the proposed model only through simulation. ORCA is the primary method, against which all the state-of-the-art techniques are evaluated. This article provides a comparison between different methods used for multi-robot collision avoidance. It discusses if the methods used are focused on safety or path planning. It also sheds light on the limitations of the studies included and possible future directions.