Multi-Goal Path Planning for Robotic Agents With Discrete-Step Locomotion

The paper introduces a new, intrinsically discrete, path planning and collision-avoidance problem, with multiple robots and multiple goals. The issue arises in the operation of the novel Swing and Dock (SaD) locomotion for a material handling system. Its agents traverse a base grid by sequences of rotations (swings) around fixed pins. Each agent must visit an array of goal positions in minimal time while avoiding collisions. The corresponding off-line path-planning problem is NP-hard. We model the system by an extended temporal graph and introduce two integer linear programming (ILP) formulations for the minimization of the makespan, with decision variables on the nodes and the edges, respectively. Both optimizations are constrained and favor idling over detours to reduce mechanical wear. The ILP formulations, tailored to the SaD system, are general enough to be applicable for many other single- and multi-agent problems over discretized networks. We have implemented the ILPs with a gurobi solver. Computational results demonstrate and compare the effectiveness of the two formulations.

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Collision-Free Motion Planning for an Aligned Multiple-turret System Operating in Extreme Environment

Robotica ◽

10.1017/s026357472100076x ◽

2021 ◽

pp. 1-30

Author(s):

Ümit Yerlikaya ◽

R.Tuna Balkan

Keyword(s):

Path Planning ◽

Extreme Environment ◽

Configuration Spaces ◽

Planning Problem ◽

Different Types ◽

Planning Algorithm ◽

Line Path ◽

Path Planning Algorithm ◽

Path Planning Problem ◽

System Operating

Abstract Instead of using the tedious process of manual positioning, an off-line path planning algorithm has been developed for military turrets to improve their accuracy and efficiency. In the scope of this research, an algorithm is proposed to search a path in three different types of configuration spaces which are rectangular-, circular-, and torus-shaped by providing three converging options named as fast, medium, and optimum depending on the application. With the help of the proposed algorithm, 4-dimensional (D) path planning problem was realized as 2-D + 2-D by using six sequences and their options. The results obtained were simulated and no collision was observed between any bodies in these three options.

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Multi-agent Path Planning Problem Under a Multi-objective Optimization Framework

Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-030-53829-3_1 ◽

2020 ◽

pp. 5-14

Author(s):

Izabela Nielsen ◽

Grzegorz Bocewicz ◽

Subrata Saha

Keyword(s):

Path Planning ◽

Planning Problem ◽

Multi Objective Optimization ◽

Multi Objective ◽

Optimization Framework ◽

Multi Agent ◽

Path Planning Problem

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Optimum path planning of robot arms

Robotica ◽

10.1017/s0263574700016350 ◽

1987 ◽

Vol 5 (4) ◽

pp. 323-331 ◽

Cited By ~ 3

Author(s):

V. Braibant ◽

M. Geradin

Keyword(s):

Path Planning ◽

Industrial Robot ◽

Planning Problem ◽

Numerical Application ◽

Optimum Path ◽

On Line ◽

Physical Limitations ◽

Line Path ◽

Path Planning Problem ◽

Mixed Nature

SUMMARYThe optimum control of an industrial robot can be achieved by splitting the problem into two tasks: off-line programming of an optimum path, followed by an on-line path tracking.The aim of this paper is to address the numerical solution of the optimum path planning problem. Because of its mixed nature, it can be expressed either in terms of Cartesian coordinates or at joint level.Whatever the approach adopted, the optimum path planning problem can be formulated as the problem of minimizing the overall time (taken as objective function) subject to behavior and side constraints arising from physical limitations and deviation error bounds. The paper proposes a very general optimization algorithm to solve this problem, which is based on the concept of mixed approximation.A numerical application is presented which demonstrates the computational efficiency of the proposed algorithm.

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Orientation Planning for Multi-Agents With Discrete-Step Locomotion and Multiple Goals

Volume 5A: 42nd Mechanisms and Robotics Conference ◽

10.1115/detc2018-86147 ◽

2018 ◽

Cited By ~ 1

Author(s):

Keerthi Sagar ◽

Dimiter Zlatanov ◽

Matteo Zoppi ◽

Cristiano Nattero ◽

Sreekumar Muthuswamy

Keyword(s):

Path Planning ◽

Flexible Manufacturing ◽

Material Handling ◽

Planning Problem ◽

Robot System ◽

Base Surface ◽

Localization And Mapping ◽

Planar Rotation ◽

Coordinated Path Planning ◽

Path Planning Problem

The paper addresses the coordinated path planning of mobile agents with multiple goal positions and orientations in a plane. The targeted multi-robot system uses discrete locomotion ensuring uncertainty-free localization and mapping as well as simple and robust control. It is suitable for material-handling, reconfigurable-fixturing, and mobile-manipulation tasks in a flexible-manufacturing environment. Using its three leg, and matching pin-socket couplings with the base surface, each agent either stands fixed or strides along via “Swing and Dock” (SaD) locomotion. Each mounting pin can serve both as a connecting-locking device and as a pivot of a planar rotation. Previous work offered planning solutions only for the agents’ positions. In reality, the orientation in which the agent arrives at the goal is very important because neither robot workspaces nor workcell geometries have axial symmetry. Herein, we provide for the required orientational planning by labelling the agent’s legs to keep track of its rotation. Integer Linear Programming (ILP) is used to model the path planning problem in the so augmented configuration space. The mathematical formulations are implemented and tested using a GUROBI solver. Computational results display the effectiveness of the approach.

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Cooperative-competitive game based approach to the local path planning problem of distributed multi-agent systems

2020 European Control Conference (ECC) ◽

10.23919/ecc51009.2020.9143792 ◽

2020 ◽

Author(s):

Quan Yuan ◽

Shuai Li ◽

Chen Wang ◽

Guangming Xie

Keyword(s):

Path Planning ◽

Planning Problem ◽

Multi Agent Systems ◽

Agent Systems ◽

Competitive Game ◽

Local Path Planning ◽

Multi Agent ◽

Local Path ◽

Path Planning Problem

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Intelligent Exploration Approaches Based on Utility Functions Optimization for Multi-Agent Environment Applications

Applied Sciences ◽

10.3390/app11052408 ◽

2021 ◽

Vol 11 (5) ◽

pp. 2408

Author(s):

José Oñate-López ◽

Loraine Navarro ◽

Christian G. Quintero M. ◽

Mauricio Pardo

Keyword(s):

Neural Networks ◽

Genetic Algorithms ◽

Path Planning ◽

Utility Function ◽

Indoor Environment ◽

Planning Problem ◽

Multi Agent ◽

The Individual ◽

Intelligent Approach ◽

Path Planning Problem

In this work, the problem of exploring an unknown environment with a team of agents and search different targets on it is considered. The key problem to be solved in multiple agents is choosing appropriate target points for the individual agents to simultaneously explore different regions of the environment. An intelligent approach is presented to coordinate several agents using a market-based model to identify the appropriate task for each agent. It is proposed to compare the fitting of the market utility function using neural networks and optimize this function using genetic algorithms to avoid heavy computation in the Non-Polynomial (NP: nondeterministic polynomial time) path-planning problem. An indoor environment inspires the proposed approach with homogeneous physical agents, and its performance is tested in simulations. The results show that the proposed approach allocates agents effectively to the environment and enables them to carry out their mission quickly.

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