Designing Adaptive Motor Control Circuitry for Swimming Biohybrid Robots
Abstract
Autonomous robots are of relevance to a variety of DoD and navy objectives, as such machines can augment or replace the need to deploy human beings in unknown and unpredictable environments. Compliant actuators that match the form, flexibility, and function of skeletal muscle are of significant interest in powering the next-generation of adaptive robots for real-world applications. However, abiotic actuators have yet to match muscle#s energy efficiency or its ability to dynamically adapt to gain-of-function cues, such as exercise, and loss-of-function cues, such as damage. Optimizing for a robust, efficient, and adaptive compliant actuator thus makes muscle a compelling choice for powering engineered systems.We have established protocols for engineering skeletal muscle that generates force in response to electrical or light stimulation. Engineered muscle adapts its form and function to changing environmental loads, with exercised tissue generating larger forces than untrained tissue. Furthermore, these actuators can heal from damage and completely recover force production. These advances have shown that engineered muscle outperforms abiotic actuators in many key aspects and has the potential to match the resilience and adaptability of natural muscle. Despite these advantages, biohybrid machines face several fundamental limitations that prevent their use as autonomous untethered underwater vehicles for applications of relevance to the ONR.We propose developing the first autonomous swimming biohybrid robot that is capable of on/off functionality with programmable speed and exercise-mediated performance adaptation, demonstrates environmentally-responsive neural control of swimming trajectory, and integrates closed-loop feedback. We will accomplish this goal by addressing fundamental scientific challenges across multiple domains that have the potential to generate robust, reproducible, untethered swimming powered by skeletal muscle. In Objective 1 of our proposal, we will design a bio-inspired swimming robot powered by independent fins that enable different modes and speeds of locomotion. We will leverage exercise to regulate muscle strength and endurance, optimizing performance for different applications. Objective 2 will focus on integrating motor neuron circuitry with our robots to demonstrate high-resolution spatiotemporal control offins and enable 3D steering. Furthermore, we will deploy genetic engineering tools to manufacture robots that sense environmental cues and guide autonomous navigation through dynamic environments. In Objective 3, we will integrate resistive sensors with our biohybrid robots that detect the rate and degree of muscle activation. The outputs of these sensors will modulate input control to antagonist muscles, improving the efficiency of swimming and demonstrating the first example of closed-loop feedback in a biohybrid machine. The knowledge products that will be generated by our multidisciplinary collaborative researchprogram will advance fundamental understanding of biohybrid actuators, with a specific focus on untethered swimming machines. Our research will establish design rules and principles, as well as a robust scalable design and manufacturing process, for deploying neuromuscular actuators as functional components in swimming machines.Potential DoD applications include exploratory swimming robots for surveillance, untethered machines for detecting and neutralizing threats in aquatic environments, and dexterous grippers for manipulating complex objects in underwatersettings. Our goal is to advance fundamental science in biohybrid actuators with the potential to enhance the safety, efficiency, and impact of DoD and navy missions in the coming years.Approved for Public Release
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 15, 2023
- Source ID
- N000142412060
Entities
People
- Ritu Raman
Organizations
- Massachusetts Institute of Technology
- Office of Naval Research
- United States Navy