6 accepted papers
Robot manipulation tasks involve direct interactions with objects, which can be viewed as dynamic changes to the robot’s kinematic chain. Morphology-aware learning frameworks, in which robot embodiment is explicitly modeled, do not account for these object-induced changes in their architectures. We …
Operating high degree of freedom robots can be difficult for users of wheelchair mounted robotic manipulators. Mode switching in Cartesian space has several drawbacks such as unintuitive control reference frames, separate translation and orientation control, and limited movement capabilities that hi
One of the critical aspects of assistive robotics is to provide a control system of a high-dimensional robot from a low-dimensional user input (i.e. a 2D joystick). Data-driven teleoperation seeks to provide an intuitive user interface called an action map to map the low dimensional input to robot v…
Movement primitives are trainable parametric models that reproduce robotic movements starting from a limited set of demonstrations. Previous works proposed simple linear models that exhibited high sample efficiency and generalization power by allowing temporal modulation of move-ments (reproducing m…
Identifying an appropriate task space can simplify solving robotic manipulation problems. One solution is deploying control algorithms in a learned low-dimensional action space. Linear and nonlinear action mapping methods have trade-offs between simplicity and the ability to express motor commands o…
Designing adaptable control laws that can transfer between different robots is a challenge because of kinematic and dynamic differences, as well as in scenarios where external sensors are used. In this work, we empirically investigate a neural networks ability to approximate the Jacobian matrix for…