Soft robotics with a focus on sensing.
Residual Physics for Grasp Failure Prediction
Prediction of grasping success is not a solved problem, with current research focusing on the grasp stability during lifting an object, which is much less then human intuition can do. Human intuition can assess the extent of possible movements, that can be done without losing a grasp of an object. The project attempts to produce an algorithm, which can analyze trajectory plans for a robotic arm and decide if the grasp would remain stable, based on tactile information, series of waypoints, and estimates of object mass and inertia. The chosen approach is to use residual physics, where a coarse physical model is complemented by residua l computed by a neural network. The project hopes to enable choosing optimal paths and maximum speeds for not optimal grasps.
To be confirmed