Soft Robotics
Neural Sensorimotor Control
How does an octopus arm localize and reach a target? We provide a biophysical model of a soft octopus arm with neuromuscular control architecture and sensory system including chemosensing and proprioception. A novel feedback neuro motor control law and a novel consensus algorithm for sensing are used to locate target and generate reaching motion.
Sensory Feedback Control
Inspired by several biology observations, we propose a novel sensory feedback control law for an octopus arm. The sensory information is assumed to be the bearing along the arm and the location of the closest point to the target.
Control-Oriented Model for Bend Propagation
A control-oriented reduced order model is constructed based on a novel parametrization of the curvature of the octopus arm in order to study its bend propagation movement. The parametrization is motivated by the experimental results.
Energy Shaping Control of Soft Actuators
The energy shaping control manipulates the energy of the control system including the potential energy landscape and kinetic energy such that it can stabilizes the system at the designed static configuration and/or changes its transient dynamics.
Energy Based Reconstruction of Soft Actuators
The energy based reconstruction of soft actuators provides a both theoretical and practical algorithm to recover internal strains including all six modes of deformations (normal/binormal bending and shear, twist and stretch). The method is implemented on the soft robot platform: BR2 and it shows high accuracy and robustness under limited data measurements.
Muscle Model of an Octopus Arm
CyberOctopus is a computational analog to living octopuses that can adapt, learn and evolve to novel tasks, situations and environments. Our team is currently modeling the muscular structure of an octopus' arm so that we can understand its various behaviors including reaching, grasping and crawling.
Optimal Control
In order to investigate the potential optimality behind some stereotypical octopus arm movements, we formulated a free endpoint optimal control problem to minimize an objective function by using the Maximum Principle for the Hamiltonian control system in the infinite-dimensional settings.