Simulation Platform for Autonomous Aerial Manipulation in Dynamic Environments
This provides a safer and more efficient testing environment for researchers and engineers working on aerial manipulation, though it is incremental as it builds on existing simulation and algorithm integration methods.
The authors tackled the problem of costly and risky real-world testing for aerial manipulation algorithms by designing a modular simulation platform, which enabled autonomous aerial grasping with integrated perception, planning, and control modules, verified through simulations.
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.