A New Multirobot Path Planning With Priority Order Based on the Generalized Voronoi Diagram

Abstract

This paper proposes a new path planning method called the priority order navigation algorithm (PONA) for multi-robot navigation in a large flat space. The PONA can guarantee collision-free and efficient travel in the space with fixed or/and dynamic obstacles. The priority order of robots is assigned by the user based on the importance degree of the robots' tasks and the objective is to make the higher priority robot reach its target faster than the lower priority robot. This study uses the generalized Voronoi diagram (GVD) to establish the initial map for PONA and links the navigation points in GVD to plan the path for each robot. Further, we modify the navigation point links to shorten feasible paths for the lower priority robot and its shortest two feasible paths can be switched to each other based on a certain condition to avoid hitting the higher priority robot. The proposed PONA is compared to several benchmark path planning methods, which are the shortest distance algorithm (SDA) and reciprocal orientation algorithm (ROA), in the simulation section and it is found that the PONA can reduce the average length of the trajectory by more than 10% compared with ROA and SDA.INDEX TERMS Voronoi diagram, Yen's algorithm, multi-robot path planning, collision-free, path-priority order.

Path Planning Techniques for Real-Time Multi-Robot Systems: A Systematic Review

“…Another challenge is the number of robots in the system since increasing the number of agents will affect the performance and the efficiency of the proposed technique in finding the optimal path. For instance, the PONA algorithm proposed in [74] does not guarantee good performance in a system with more than eight robots.…”

An Evolutionary Navigation Algorithm for Multi-Robot With Priority Order

“…Frankly, neither SP-1, SP-2, nor SP-3 is the real shortest path if the paths must be along the navigation links. Using the method of [10], for any robot, we can find a shorter path MSP − λ which is shorter than SP − λ corresponding to different λs as shown in Fig. 8, where the green paths are called the modified SP-1 (denoted as MSP-1), the modified SP-2 (denoted as MSP-2), and the modified SP-3 (denoted as MSP-3); besides, SP-1 and SP-2 are shortened to the same path MSP-1 or MSP-2 for R2.…”

“…9, SP-1, SP-2, and SP-3 are shortened to the MSP-1, MSP-2, and MSP-3 for R4, respectively. In PONA [10], the authors only considered two MSPs, i.e., MSP-1 and MSP-2. There will be a problem below.…”

“…For instance, in paper [9], the navigation strategy with path priority (NSPP) was proposed such that robots with higher path priority have a shorter path than robots with lower path priority. A priority order navigation algorithm (PONA) was proposed by [10] to solve the problem of NSPP and give a shorter average travel length for all robots, but the target arrival order is not ensured to match the priority order. The paper [11] introduced an algorithm to implement cooperative path planning for multiple robots and dynamically adjusted the priority of robots by using the last path length constraint.…”

“…In this paper, we will propose a new priority order navigation algorithm (PONA2.0) that improves the result of PONA in [10] and ensures each robot can reach its target in a two-dimensional flat space without any collision efficiently. We also suppose the speed of all robots is the same, and there is no-slip between the tire of the robot and the floor during motion.…”