Scalable Decentralized Multi-Robot Trajectory Optimization in Continuous-Time

被引：7

作者：

Kandhasamy, Sivanathan ^{[1
]}

Kuppusamy, Vinayagam Babu ^{[2
]}

Krishnan, Shravan ^{[1
]}

机构：

[1] SRM Inst Sci & Technol, Fac Engn & Technol, Dept Mechatron Engn, Autonomous Syst Lab, Kanchipuram 603203, India

[2] SRM Inst Sci & Technol, Fac Engn & Technol, Dept Mechatron Engn, Kanchipuram 603203, India

来源：

IEEE ACCESS | 2020年 / 8卷

关键词：

Collision avoidance; Planning; Prediction algorithms; Trajectory optimization; Robot sensing systems; Multi-robot system; trajectory optimization; obstacle avoidance; model predictive control; COLLISION-AVOIDANCE; GENERATION; OBSTACLES;

D O I：

10.1109/ACCESS.2020.3024685

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article presents a decentralized algorithm that generates continuous-time trajectory online for a swarm of robots based upon model predictive control. To generate collision-free trajectory, temporally distinct safe regions are formed such that the robots are confined to move within these safe regions to avoid collisions with one another. The distinct safe regions are temporally linked by generating a B-spline. Additionally, to ensure that collisions are avoided, collision-regions that the robots have to stay outside are also generated distinctly. A non linear program (NLP) with an objective to make the robots stay outside the collision-regions and stay within the safe regions is formulated. The algorithm was tested in simulations on Gazebo with aerial robots. The simulated results suggest that the proposed algorithm is computationally efficient and can be used for online planning in moderate sized multi-robot systems.

引用

页码：173308 / 173322

页数：15

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