TY - GEN
T1 - AeroBotSim
T2 - 7th International Conference on Cognitive Systems and Information Processing, ICCSIP 2022
AU - Du, Jianrui
AU - Fan, Yingjun
AU - Wang, Kaidi
AU - Feng, Yuting
AU - Yu, Yushu
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Aircraft simulator
KW - Contact simulation
KW - High-fidelity Images
KW - Physical interaction
UR - http://www.scopus.com/inward/record.url?scp=85149851581&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-0617-8_19
DO - 10.1007/978-981-99-0617-8_19
M3 - Conference contribution
AN - SCOPUS:85149851581
SN - 9789819906161
T3 - Communications in Computer and Information Science
SP - 274
EP - 287
BT - Cognitive Systems and Information Processing - 7th International Conference, ICCSIP 2022, Revised Selected Papers
A2 - Sun, Fuchun
A2 - Cangelosi, Angelo
A2 - Zhang, Jianwei
A2 - Yu, Yuanlong
A2 - Liu, Huaping
A2 - Fang, Bin
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 17 December 2022 through 18 December 2022
ER -