Simulation Platform for Autonomous Aerial Manipulation in Dynamic Environments

TL;DR

This paper introduces a modular simulation platform for autonomous aerial manipulation, enabling safe testing and development of algorithms for obstacle avoidance and target grasping in dynamic environments.

Contribution

A novel modular simulation platform for aerial manipulators that integrates perception, planning, and control algorithms for autonomous grasping tasks.

Findings

Successfully verified autonomous grasping in simulations

Demonstrated obstacle avoidance capabilities

Platform's modular design allows easy extension

Abstract

The aerial manipulator (AM) is a systematic operational robotic platform in high standard on algorithm robustness. Directly deploying the algorithms to the practical system will take numerous trial and error costs and even cause destructive results. In this paper, a new modular simulation platform is designed to evaluate aerial manipulation related algorithms before deploying. In addition, to realize a fully autonomous aerial grasping, a series of algorithm modules consisting a complete workflow are designed and integrated in the simulation platform, including perception, planning and control modules. This framework empowers the AM to autonomously grasp remote targets without colliding with surrounding obstacles relying only on on-board sensors. Benefiting from its modular design, this software architecture can be easily extended with additional algorithms. Finally, several simulations are performed to verify the effectiveness of the proposed system.