3 accepted papers
Detecting and localizing contacts acting on a manipulator is a relevant problem for manipulation tasks like grasping, since contact information can be helpful for recovering from collisions or for improving the grasping performance itself. In this work, we present a solution for contact point locali…
Recursive state estimation is often used to estimate a probability density function of a specific state, e.g. a robot's pose, over time. Compared to Kalman filters, Sequential Monte Carlo (SMC) methods are less constrained in regard to state propagation and update model definition, which makes it ea…
A model-based Machine Learning (ML) approach is presented to detect and localize external contacts on a 6 degree of freedom (DoF) serial manipulator. This approach only requires the use of proprioceptive sensors (joint positions, velocities and one-dimensional (ID) joint torques already available in…