TY - GEN
T1 - Locust-Inspired Timing Strategy for Wing Deployment in Jump-Fly Robots
AU - Si, Yunhao
AU - Jin, Yanzhou
AU - Jing, Chengcheng
AU - Yu, Zhiqiang
AU - Fukuda, Toshio
AU - Shi, Qing
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Small-scale robots often face challenges in traversing terrains of different scales. The combination of jumping and flying motion can enhance their obstacle-surmounting ability, and the timing of wing deployment undoubtedly plays a critical role in their jump-fly performance. However, previous studies of jump-fly robots have deployed wings speculatively at the highest point of the jump trajectory, resulting in suboptimal locomotion distance. In this study, we characterized the jump-fly motion of locusts and found that wing deployment timing is regulated by both airspeed and body angle. To verify the effect of this discovery on jump-fly robot motion, we constructed a jump-fly robot model in MATLAB and found that deploying wings based on the discovered airspeed-body angle relationship results in the farthest locomotion distance. Our findings provide valuable insights for improving the locomotion ability of jump-fly robots.
AB - Small-scale robots often face challenges in traversing terrains of different scales. The combination of jumping and flying motion can enhance their obstacle-surmounting ability, and the timing of wing deployment undoubtedly plays a critical role in their jump-fly performance. However, previous studies of jump-fly robots have deployed wings speculatively at the highest point of the jump trajectory, resulting in suboptimal locomotion distance. In this study, we characterized the jump-fly motion of locusts and found that wing deployment timing is regulated by both airspeed and body angle. To verify the effect of this discovery on jump-fly robot motion, we constructed a jump-fly robot model in MATLAB and found that deploying wings based on the discovered airspeed-body angle relationship results in the farthest locomotion distance. Our findings provide valuable insights for improving the locomotion ability of jump-fly robots.
UR - http://www.scopus.com/inward/record.url?scp=85173605691&partnerID=8YFLogxK
U2 - 10.1109/RCAR58764.2023.10250097
DO - 10.1109/RCAR58764.2023.10250097
M3 - Conference contribution
AN - SCOPUS:85173605691
T3 - Proceedings of the 2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023
SP - 44
EP - 50
BT - Proceedings of the 2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023
Y2 - 17 July 2023 through 20 July 2023
ER -