Online Trajectory Planning and Collision Avoidance for a Group of Robots Using Distributed Model Predictive Control

被引：1

作者：

Costantini, Giuliano ^{[1
]}

Rostami, Ramin ^{[1
]}

Goerges, Daniel ^{[1
]}

机构：

[1] Univ Kaiserslautern, Dept Elect & Comp Engn, Erwin Schrodinger Str 12, D-67663 Kaiserslautern, Germany

来源：

ADVANCES IN SERVICE AND INDUSTRIAL ROBOTICS | 2020年 / 980卷

关键词：

Autonomous vehicles; Unicycle robots; Trajectory planning; Collision avoidance; Distributed model predictive control; EXPONENTIAL STABILIZATION; MOBILE ROBOTS; SYSTEMS;

D O I：

10.1007/978-3-030-19648-6_28

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper the trajectory planning problem for unicycle robots is studied. This problem is particularly difficult to solve online due to its inherently nonlinear and nonconvex structure. The first aim of the paper is to overcome these difficulties using model predictive control (MPC) when a single robot is considered. Several requirements must be fulfilled by the optimal trajectory, such as respecting physical limitations as well as track constraints. The second aim of the paper is to extend the results to a group of robots using distributed MPC providing formation control and inter-robot collision avoidance.

引用

页码：240 / 249

页数：10

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