Obstacle Avoidance Strategy using Onboard Stereo Vision on a Flapping Wing MAV

Research output: Contribution to journalArticleScientificpeer-review

19 Citations (Scopus)

Abstract

The development of autonomous lightweight MAVs, capable of navigating in unknown indoor environments, is one of the major challenges in robotics. The complexity of this challenge comes from constraints on weight and power consumption of onboard sensing and processing devices. In this paper, we propose the 'Droplet' strategy, an avoidance strategy based on stereo vision inputs that outperforms reactive avoidance strategies by allowing constant speed maneuvers while being computationally extremely efficient, and which does not need to store previous images or maps. The strategy deals with nonholonomic motion constraints of most fixed and flapping wing platforms, and with the limited field-of-view of stereo camera systems. It guarantees obstacle-free flight in the absence of sensor and motor noise. We first analyze the strategy in simulation, and then show its robustness in real-world conditions by implementing it on a 20-gram flapping wing MAV.

Original languageEnglish
Article number7919189
Pages (from-to)858-874
Number of pages17
JournalIEEE Transactions on Robotics
Volume33
Issue number4
DOIs
Publication statusPublished - 1 Aug 2017

Keywords

  • Aerial robotics
  • collision avoidance
  • micro robots
  • stereo vision

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