activity
20192022
most citedAn Active Sense and Avoid System for Flying Robots in Dynamic Environments

45 citations · 52 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2022★ 1 cited

Obstacle Avoidance of Resilient UAV Swarm Formation with Active Sensing System in the Dense Environment

Peng Peng, Wei Dong, Gang Chen +1

This paper proposes a perception-shared and swarm trajectory global optimal (STGO) algorithm fused UAVs formation motion planning framework aided by an active sensing system. First…

cs.RO2022

Risk-aware Trajectory Sampling for Quadrotor Obstacle Avoidance in Dynamic Environments

Gang Chen, Peng Peng, Peihan Zhang +1

Obstacle avoidance of quadrotors in dynamic environments is still a very open problem. Current works commonly leverage traditional static maps to represent static obstacles and the…

cs.RO2022★ 2 cited

Continuous Occupancy Mapping in Dynamic Environments Using Particles

Gang Chen, Wei Dong, Peng Peng +2

Particle-based dynamic occupancy maps were proposed in recent years to model the obstacles in dynamic environments. Current particle-based maps describe the occupancy status in dis…

cs.RO2021★ 1 cited

Agile Formation Control of Drone Flocking Enhanced with Active Vision-based Relative Localization

Peihan Zhang, Gang Chen, Yuzhu Li +1

The vision-based relative localization can provide effective feedback for the cooperation of aerial swarm and has been widely investigated in previous works. However, the limited f…

cs.RO2020★ 45 cited

An Active Sense and Avoid System for Flying Robots in Dynamic Environments

Gang Chen, Wei Dong, Xinjun Sheng +2

This paper investigates a novel active-sensing-based obstacle avoidance paradigm for flying robots in dynamic environments. Instead of fusing multiple sensors to enlarge the field…

cs.RO2019★ 3 cited

Learning to Navigate from Simulation via Spatial and Semantic Information Synthesis with Noise Model Embedding

Gang Chen, Hongzhe Yu, Wei Dong +3

While training an end-to-end navigation network in the real world is usually of high cost, simulation provides a safe and cheap environment in this training stage. However, trainin…