Cooperative Path Planning for Multiple Mobile Robots via HAFSA and an Expansion Logic Strategy

Abstract

The cooperative path planning problem of multiple mobile robots in an unknown indoor environment is considered in this article. We presented a novel obstacle avoidance and real-time navigation algorithm. The proposed approach consisted of global path planning and local path planning via HAFSA (hybrid artificial fish swarm algorithm) and an expansion logic strategy. Meanwhile, a kind of scoring function was developed, which shortened the time of local path planning and improved the decision-making ability of the path planning algorithm. Finally, using STDR (simple two dimensional robot simulator) and RVIZ (robot operating system visualizer), a multiple mobile robot simulation platform was designed to verify the presented real-time navigation algorithm. Simulation experiments were performed to validate the effectiveness of the proposed path planning method for multiple mobile robots.

The boundary node method for multi‐robot multi‐goal path planning problems

“…In previous research work, different methods were used to solve the multi-robot multi-goal path planning problem, that is, the authors in Huang et al (2019) considered the cooperative path planning problem of multiple mobile robots in an unknown indoor environment. They proposed a novel obstacle avoidance and real-time navigation algorithm.…”

“…Recently, using multiple mobile robots rather than a single mobile robot has attracted many researchers' attention (Huang et al, 2019), and it has been widely used in industrial plants and warehouses (Liu et al, 2010). Optimizing the paths of the mobile robots that move simultaneously is a challenging problem (Nazarahari et al, 2019).…”

Special Feature on Advanced Mobile Robotics

“…[1] showed that the task can be transformed to an optimal assignment problem with mathematical modeling and suboptimal relaxations are available for the solution. Multiple mobile robots often experience path planning problems and a real-time navigation algorithm with obstacle avoidance has been suggested by Huang et al [2] based on a fish swarm algorithm to guide two phases of global and local path planning. In some environments, multiple mobile robots together manipulate an object in a cooperative way.…”

NPQ‐RRT ∗: An Improved RRT ∗ Approach to Hybrid Path Planning

“…As a typical representative of agents, multiple autonomous robots, including unmanned aerial vehicles (UAVs), automatic ground vehicles (AGVs), and unmanned underwater vehicles (UUVs), play an important role in military and civil fields [5][6][7][8][9][10][11][12][13]. To ensure robots carry out related work in our life efficiently and safely, path planning, which means finding a feasible path without collisions from the starting state to the target state, has been a hot research point in the field of mobile robot applications [14][15][16][17][18]. At present, path planning algorithms can be divided into global path planning algorithms and local path planning algorithms, which mainly include geometric algorithms, artificial potential field algorithms, grid-based search algorithms, and samplingbased algorithms.…”