Bio-inspired inverted landing strategy in a small aerial robot using policy gradient

Pan Liu, Junyi Geng, Yixian Li, Yanran Cao, Yagiz E. Bayiz, Jacob Willem Langelaan, Bo Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Landing upside down on a ceiling is challenging as it requires a flier to invert its body and land against the gravity, a process that demands a stringent spatiotemporal coordination of body translational and rotational motion. Although such an aerobatic feat is routinely performed by biological fliers such as flies, it is not yet achieved in aerial robots using onboard sensors. This work describes the development of a bio-inspired inverted landing strategy using computationally efficient Relative Retinal Expansion Velocity (RREV) as a visual cue. This landing strategy consists of a sequence of two motions, i.e. an upward acceleration and a rapid angular maneuver. A policy search algorithm is applied to optimize the landing strategy and improve its robustness by learning the transition timing between the two motions and the magnitude of the target body angular velocity. Simulation results show that the aerial robot is able to achieve robust inverted landing, and it tends to exploit its maximal maneuverability. In addition to the computational aspects of the landing strategy, the robustness of landing is also significantly dependent on the mechanical design of the landing gear, the upward velocity at the start of body rotation, and timing of rotor shutdown.

Original languageEnglish (US)
Title of host publication2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7772-7777
Number of pages6
ISBN (Electronic)9781728162126
DOIs
StatePublished - Oct 24 2020
Event2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020 - Las Vegas, United States
Duration: Oct 24 2020Jan 24 2021

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
Country/TerritoryUnited States
CityLas Vegas
Period10/24/201/24/21

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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