The Navigational Toolkit in Insects and Bio-inspired Strategies for Aerial Robots
Abstract
Flying in real environments, that are densely cluttered with obstacles, is a major challenge limiting the proliferation of aerial robotic technology. Insects, in contrast, are capable of precise flight and navigation through cluttered terrain despite carrying only tiny sensory and motor systems. An enabling trait to accomplish such tasks is the capacity to rapidly process ambient visual information and generate motor commands to effectuate appropriate flight manoeuvres. Understanding the strategies implemented by flying insects at the information processing and motor-control levels is vital in developing a general framework for the implementation of effective bio-inspired navigation strategies on robotic platforms. Honeybees, being adept flyers, are ideal biological systems for gaining a better understanding of aerial locomotion through cluttered environments, not only because they are readily amenable to experimentation, but also because of the significant body of literature that exists on the biomechanics and neuroethology of their flight. This project will systematically probe critical features of the action-perception loop within insects, to uncover the salient vision-based strategies that are used for guidance of flight in cluttered environments. PIs will seek to highlight salient cues that might aid in spatial perception, collision anticipation and path planning using relatively basic sensory systems and limited processing. Specifically, PIs will address the behavioural adjustments and visuomotor strategies used by bees for spatial perception of static and dynamics obstacles, and navigation through various levels of clutter and spatial properties of the environment. Results from the biological experiments will be used to develop sensory and information processing frameworks for implementation in miniature robotic systems which will allow them to navigate autonomously in complex environments even when GPS positioning is denied. Such capabilities will expand the operational domain and potential applications for small autonomous vehicles while improving our knowledge of insect locomotion.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 17, 2022
- Source ID
- FA23862114075
Entities
People
- Sridhar Ravi
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of New South Wales