Robust and Efficient Trajectory Planning for Formation Flight in Dense Environments-Reference-Cited by-同舟云学术

Robust and Efficient Trajectory Planning for Formation Flight in Dense Environments

Published:2023-12 Issue:6 Volume:39 Page:4785-4804
ISSN:1552-3098
Container-title:IEEE Transactions on Robotics
language:
Short-container-title:IEEE Trans. Robot.

Author:

Quan Lun¹^ORCID,Yin Longji¹^ORCID,Zhang Tingrui¹^ORCID,Wang Mingyang¹^ORCID,Wang Ruilin¹^ORCID,Zhong Sheng¹^ORCID,Zhou Xin¹^ORCID,Cao Yanjun¹^ORCID,Xu Chao¹^ORCID,Gao Fei¹^ORCID

Affiliation:

1. State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8860/10352149/10219410.pdf?arnumber=10219410

Reference53 articles.

1. Decoupled multiagent path planning via incremental sequential convex programming

2. Fast, On-line Collision Avoidance for Dynamic Vehicles Using Buffered Voronoi Cells

3. Model Predictive Trajectory Tracking and Collision Avoidance for Reliable Outdoor Deployment of Unmanned Aerial Vehicles

4. Stabilisation of infinitesimally rigid formations of multi-robot networks

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