Motion Planning Of Multiple Robots Research Articles

Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated Algorithm

Path planning is crucial in the scheduling and motion planning of multiple robots. However, solving multi-robot path-planning problems efficiently and quickly is challenging due to their high complexity and long computational time, especially when dealing with many robots. This paper presents a unified mathematical model and algorithm for the path planning of multiple robots moving from one formation to another in an area with obstacles. The problem was initially simplified by constructing a cost matrix, and then the route planning was achieved by integrating an elite enhanced multi-population genetic algorithm and an ant colony algorithm. The performance of the proposed planning method was verified through numerical simulations in various scenarios. The findings indicate that this method exhibits high computational efficiency and yields a minimal overall path distance when addressing the path-planning problem of a multi-robot formation reconstruction. As a result, it holds promising potential for the path-planning problem of a multi-robot formation reconstruction.

Integrated real-time task and motion planning for multiple robots under path and communication uncertainties

SUMMARYWe consider a problem where robots are given a set of task locations to visit with coarsely known distances. The robots must find the task ordering that reduces the overall distance to visit the tasks. We propose an abstraction that models the uncertainty in the paths, and a Markov Decision Process-based algorithm that selects paths that reduces the expected distance to visit the tasks. We also describe a distributed coordination algorithm to resolve path conflicts. We have shown that our task selection is optimal, our coordination is deadlock-free, and have experimentally verified our approach in hardware and simulation.

2P1-V10 モード切り替えを行う複数移動ロボットのモンテカルロ法を用いた協調押し動作の動作計画

2P1-V10 モード切り替えを行う複数移動ロボットのモンテカルロ法を用いた協調押し動作の動作計画

Conflict free coordinated path planning for multiple robots using a dynamic path modification sequence

In this paper, a practically viable approach for conflict free, coordinated motion planning of multiple robots is proposed. The presented approach is a two phase decoupled method that can provide the desired coordination among the participating robots in offline mode. In the first phase, the collision free path with respect to stationary obstacles for each robot is obtained by employing an A* algorithm. In the second phase, the coordination among multiple robots is achieved by resolving conflicts based on a path modification approach. The paths of conflicting robots are modified based on their position in a dynamically computed path modification sequence (PMS). To assess the effectiveness of the developed methodology, the coordination among robots is also achieved by different strategies such as fixed priority sequence allotment for motion of each robot, reduction in the velocities of joints of the robot, and introduction of delay in starting of each robot. The performance is assessed in terms of the length of path traversed by each robot, time taken by the robot to realize the task and computational time. The effectiveness of the proposed approach for multi-robot motion planning is demonstrated with two case studies that considered the tasks with three and four robots. The results obtained from realistic simulation of multi-robot environment demonstrate that the proposed approach assures rapid, concurrent and conflict free coordinated path planning for multiple robots.

Multi-Agent System for Off-Line Coordinated Motion Planning of Multiple Industrial Robots

This article presents an agent based framework for coordinated motion planning of multiple robots. The emerging paradigm of agent based systems is implemented to address various issues related to safe and fast task execution when multiple robots share a common workspace. In the proposed agent based framework, each issue vital for coordinated motion planning of multiple robots and every robot participating in coordinated task is considered as an agent. The identified agents are interfaced with each other in order to incorporate the desired flexibility in the developed framework. This framework gives a complete strategy for determination of optimal trajectories of robots working in coordination with due consideration to their kinematic, dynamic and payload constraint. The complete architecture of the proposed framework and the detailed discussion on various modules are covered in this paper.

Motion planning for multiple robots with multi-mode operations via disjunctive graphs

SUMMARYA new approach to motion planning for multiple robots with multi-mode operations is proposed in this paper. Although sharing a common workspace, the robots are assumed to perform periodical tasks independently. The goal is to schedule the motion trajectories of the robots so as to avoid collisions among them. Rather than assigning the robots with different priorities and planning safe motion for only one robot at a time, as is done in most previous studies, an efficient method is developed that can simultaneously generate collision-free motions for the robots with or without priority assignment. Being regarded as a type of job-shop scheduling, the problem is reduced to that of finding a minimaximal path in a disjunctive graph and solved by an extension of the Balas algorithm. The superiority of this approach is demonstrated with various robot operation requirements, including “non-priority”, “with-priority”, and “multicycle” operation modes. Some techniques for speeding up the scheduling process are also presented. The planning results can be described by Gantt charts and executed by a simple “stop-and-go” control scheme. Simulation results on different robot operation modes are also presented to show the feasibility of the proposed approach.