EFRI BRAID: Resilient autonomous navigation inspired by the insect central complex and sensorimotor control motifs

Board Of Regents, Nshe, Obo University Of Nevada, Reno, Reno NV

Investigators

Abstract

The last decade has seen a substantial increase in the frequency of natural disasters including wildfires, flooding, landslides, and outbreaks of agricultural pests and diseases. Mitigating the severity of disasters will require early warning and rapid responses, both of which could be aided by reliable and inexpensive autonomous robots. Unfortunately, modern robots have difficulty responding to new environments or damage to their bodies that might occur during disaster response. In contrast, living systems are remarkably adept at quickly adjusting their behavior to new situations thanks to redundancy and flexibility within the sensory and muscle control systems. Scientific discoveries in fruit flies have helped shed light on how these insects achieve resiliency in flight. The primary goal of this project is to translate this emerging knowledge from insect neuroscience to enable the development of more resilient robotic systems. This project builds on existing engineering theory to develop algorithms that are easy to understand and explain. As part of this project, unique research experiences will be offered to middle, high school, and undergraduate students to participate in both neuroscience and robotics research. The multidisciplinary research team will develop open-source course content to help bring neuroscience fluency to engineering students: translating neuroscience principles to engineering for enhanced resilience. A significant engineering challenge that has stymied the rollout of autonomous robotics is their lack of resilience in novel scenarios. In contrast, organisms are adept at quickly adjusting their behavior to new contexts thanks to redundancy and flexibility within their sensorimotor systems. Incorporating comparable functionality in engineered systems has proven challenging because we lack the basic knowledge for how to fuse information streams from different sensors and coordinate a large array of actuators without detailed models and constant calibrations—this sophisticated operation is achieved effortlessly by even simple animals. The overall goal of this proposal is to leverage recent neurobiological discoveries to develop new designs for autonomous robots that learn to adapt rapidly to changes in the environment or in their sensory and motor systems. The proposed approach draws inspiration from two themes found in insects: 1) the exploitation of a versatile, multisensory compass for navigation, and 2) the flexible implementation of stereotyped sensorimotor motifs in locomotion and other behaviors. The goals are to translate these concepts into engineering principles at an abstracted control-theoretic level, and then to implement and test them on functioning multirotor systems. This project is jointly funded by the Emerging Frontiers in Research and Innovation Program (BRAID) and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.