An Integrated Mechanical Intelligence and Control Approach Towards Flight Control of Aerobat

TL;DR

This paper introduces the MIMIC framework, combining mechanical intelligence and control, to enable robotic systems to mimic bat flight, demonstrating stable flight in a bio-inspired drone model.

Contribution

The paper proposes the MIMIC framework that integrates mechanical intelligence with control to replicate bat flight in robotic systems, addressing limitations of previous design paradigms.

Findings

Successful implementation of MIMIC in the Aerobat model

Demonstration of stable bat-like flight using integrated mechanical intelligence

Validation of computational structures and feedback in biomimetic flight

Abstract

Our goal in this work is to expand the theory and practice of robot locomotion by addressing critical challenges associated with the robotic biomimicry of bat aerial locomotion. Bats are known for their pronounced, fast wing articulations, e.g., bats can mobilize as many as forty joints during a single wingbeat, with some joints reaching over one thousand degrees per second in angular speed. Copying bats flight is a significant ordeal, however, very rewarding. Aerial drones with morphing bodies similar to bats can be safer, agile and energy-efficient owing to their articulated and soft wings. Current design paradigms have failed to copy bat flight because they assume only closed-loop feedback roles and ignore computational roles carried out by morphology. To respond to the urgency, a design framework called Morphing via Integrated Mechanical Intelligence and Control (MIMIC) is proposed. In this paper, using the dynamic model of Northeastern University's Aerobat, which is designed to test the effectiveness of the MIMIC framework, it will be shown that computational structures and closed-loop feedback can be successfully used to mimic bats stable flight apparatus.