Smell Driven Navigation for Soft Robotic Arms: Artificial Nose and Control

Abstract

Elephants and other animals heavily rely on the sense of smell to operate. Soft robots would also benefit from an artificial sense of smell, which could be helpful in typical soft robotic tasks such as search and rescue, pipe inspection, and all the tasks involving unstructured environments. This work proposes an artificial nose on a soft robotic arm that ensures separate smell concentration readings. We propose designing the nose to generate a one-to-one matching between the sensors' inputs and the actuators. This design choice allows us to implement a simple control strategy tailored to reach a dynamically varying smell in the environment, which we validate on a two-segment tendon-driven soft robotic arm equipped with the proposed artificial nose. We also propose and validate in simulation a control strategy for reaching tasks in the case of a stationary smell.