Modeling and control of soft robots (TU/e)

The area of soft robotics is distinguished by its diverse family of bio-inspired robots. These robotic systems range from compliant grippers emulating the morphology of the chameleon’s tongue to manipulator-like robots inspired by the elephant’s trunk, and even microscopic robots made from biological cells capable of autonomous locomotion.
‘Soft robotics’ can be seen as robots composed of soft materials that exploit their low compliance to produce continuous motion with some biological resemblance. Despite their novelty, soft robots have intrinsically more degrees-of-freedom that can be controlled or measured by a finite set of actuators and sensors. The system also has non-trivial equilibrium points, as the static configuration of the elastic body is determined by statically balancing an infinite dimensional system. As such, its hyper-flexible structure poses significant challenges for closed-loop

We are looking for students interested in modeling and control of soft robots.

Example projects:

Observer design for deformable soft robots
The aim of the project is to develop a nonlinear observer such that the deformations of an elastic structure can be dynamically reconstructed through fusing an array of sensory data, e.g., strain data, inertial data, and force data. As the continuous elastic body theoretically possesses infinite DOF’s, it is important to account for the trade-off between
the quantity of sensory data and the quality of the shape reconstruction. It might also be interesting to investigate the possibility of environmental perception (e.g., stiffness perception) through soft contact – infinitesimal deformations at the end-effector such that stiffness can be perceived. One possibility is to develop a soft structure with embedded sensing through additive manufacturing, e.g., FMD.

Using EMG to control soft robotic limbs
Robotic limbs are being used in several applications in industry, but there is also an increase in applications for individuals, such as a support device for people with muscle diseases. For using these robotic devices in close proximity with the human and it is important that the interaction is safe and that the device is not too bulky. To make the control of robots for individuals as intuitive (and non-invasive) as possible, the idea is to gather the input of the human operator by EMG. This information needs to be translated into input for the control (e.g. the desired movement). The student will study how to measure EMG signals, which details can be measured and how this information can be used to build a model to identify desired postures or actions based on these EMG signals.