5 accepted papers
Aerial manipulation provides an effective alternative to human labor in high-risk outdoor situations. Complex and variable environments demand the system to respond quickly with minimal latency to external disturbances. To address this challenge, we propose a learning-based variable whole-body model
Quadrotors, while versatile, are vulnerable to unpredictable environmental disturbances, including turbulence, gusts, and ground effects, making precise path-following control a formidable challenge. This letter introduces an adaptive neural network-based predictive control framework tailored for qu
Aerial manipulation has received increasing research interest with wide applications of drones. To perform specific tasks, robotic arms with various mechanical structures will be mounted on the drone. It results in sudden disturbances to the aerial manipulator when switching the robotic arm or inter…
Autonomous exploration plays a crucial role in robotics applications like rescue and scene reconstruction. This work addresses the challenges of autonomous exploration in intricate unknown environments by presenting a novel UAV autonomous exploration method based on a new concept of the view-region.…
Control of an aerial manipulator is challenging due to the decentralized dynamics of the aerial vehicle and the robotic arm. It is generally complex to adjust the controller of the aerial manipulator when replacing a different robotic arm. This paper presents a flexible control scheme for a quadroto…