activity
20202022
most citedDecentralized Spatial-Temporal Trajectory Planning for Multicopter Swarms

20 citations · 86 across the 18 of their papers we have counts for

collaborators

27 papers

cs.RO2022

Bearing-based Relative Localization for Robotic Swarm with Partially Mutual Observations

Yingjian Wang, Xiangyong Wen, Yanjun Cao +2

Mutual localization provides a consensus of reference frame as an essential basis for cooperation in multirobot systems. Previous works have developed certifiable and robust solver…

cs.RO2022

Dynamic Free-Space Roadmap for Safe Quadrotor Motion Planning

Junlong Guo, Zhiren Xun, Shuang Geng +3

Free-space-oriented roadmaps typically generate a series of convex geometric primitives, which constitute the safe region for motion planning. However, a static environment is assu…

cs.RO2022

Star-Convex Constrained Optimization for Visibility Planning with Application to Aerial Inspection

Tianyu Liu, Qianhao Wang, Xingguang Zhong +4

The visible capability is critical in many robot applications, such as inspection and surveillance, etc. Without the assurance of the visibility to targets, some tasks end up not b…

cs.RO20221 cited

Certifiably Optimal Mutual Localization with Anonymous Bearing Measurements

Yingjian Wang, Xiangyong Wen, Longji Yin +3

Mutual localization is essential for coordination and cooperation in multi-robot systems. Previous works have tackled this problem by assuming available correspondences between mea…

cs.RO20211 cited

Robust Trajectory Planning for Spatial-Temporal Multi-Drone Coordination in Large Scenes

Zhepei Wang, Chao Xu, Fei Gao

In this paper, we describe a robust multi-drone planning framework for high-speed trajectories in large scenes. It uses a free-space-oriented map to free the optimization from cumb…

cs.RO2021

STD-Trees: Spatio-temporal Deformable Trees for Multirotors Kinodynamic Planning

Hongkai Ye, Chao Xu, Fei Gao

In constrained solution spaces with a huge number of homotopy classes, stand-alone sampling-based kinodynamic planners suffer low efficiency in convergence. Local optimization is i…