Abstract
In the field of aerial manipulation, heterogeneous aerial systems with complex configuration become more and more popular, as they can overcome problems of traditional aircrafts in aerial manipulation. However, recent photo-realistic aircraft simulators do not support the accurate contact and collision behavior simulation of aircraft or the dynamics simulation of heterogeneous aerial systems. Besides, high-fidelity images are required in many machine learning-based perception and action algorithms. Therefore, we develop a simulator to provide a solution to aerial manipulation robots training, algorithm tests, and display: AeroBotSim. By using modular design, we decouple rendering engine and physics engine to obtain high-frequency states data while retrieving high-fidelity images. Also, we synchronize the contact information in rendering engine and the physics engine, and design interfaces to custom contact behavior for operation, separation, and recombination simulation. In this paper, we present our framework design and dynamic models of aircrafts under physical interaction. Then, we validate our simulator framework in three aspects: baseline controller in ROS, vision-based algorithm, and contact simulation respectively.
Supported by the National Natural Science Foundation of China under Grant 62173037, National Key R. D. Program of China, and State Key Laboratory of Robotics and Systems (HIT).
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Du, J., Fan, Y., Wang, K., Feng, Y., Yu, Y. (2023). AeroBotSim: A High-Photo-Fidelity Simulator for Heterogeneous Aerial Systems Under Physical Interaction. In: Sun, F., Cangelosi, A., Zhang, J., Yu, Y., Liu, H., Fang, B. (eds) Cognitive Systems and Information Processing. ICCSIP 2022. Communications in Computer and Information Science, vol 1787. Springer, Singapore. https://doi.org/10.1007/978-981-99-0617-8_19
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