Building a quadruped robot for reinforcement learning research

The goal of this project is to build the open-sourced quadruped robot called Real-Ant. To start with, the 3D models and the codes for the microcontroller as well as serial port communication are available for the robot. So the first task will be to print the components, assemble the robot and test the available codes on the robot. Then in the second stage, we will modify the robot to make it more robust so that it can tolerate mild shocks and can be run for an extended period of time without the need of tightening the screws or replacing the components. For example, we can think of adding soft legs, cushions etc. to protect the belly and the actuators. In addition, we can also simplify the design so that it can be repaired quickly if required.

Soft Robotic Hand

Robotic grasping has been studied for more than 30 years, but it is still a challenging field. Today, most robotic grippers are rigid, making it hard for them to grasp and handle irregularly shaped objects that are delicate and easily deformed such as a compact disc, an egg, or an empty plastic cup. To tackle […]

Exploiting Object Physical Properties for Grasping

In robotic manipulation, robots are required to interact with, and adapt to, unknown environments and objects. In order to successfully accomplish these tasks, robots need to identify various properties of the objects to be handled. For these reasons, identifying object models that can represent the properties of objects has become a crucial issue in robotics. […]

Safe Model Predictive Control

Safe Model Predictive Control (Safe MPC) aims to ensure that a physical system’s safety constraints are satisfied with high probability. Our research is on extending constrained MPC methods to cope with probabilistic safety constraints. We further research modeling uncertainty of dynamics to ensure safe exploration when combined with safety constraints learned in simulation, and learning powerful data-efficient surrogate models for complex dynamics.