3 accepted papers
In this paper, we propose a deep neural network that predicts the feasibility of a mixed-integer program from visual input for robot manipulation planning. Integrating learning into task and motion planning is challenging, since it is unclear how the scene and goals can be encoded as input to the le…
We present a self-supervised representation learning approach for visual reasoning and integrate it into a nonlinear program formulation for motion optimization to tackle sequential manipulation tasks. Such problems have usually been addressed by combined task and motion planning approaches, for whi
With the integration of Human-Robot Collaboration (HRC) in industrial assembly scenarios, robot systems face numerous challenges. In contrast to classic robot systems which follow a pre-programmed and fixed sequence of actions, an interaction scenario with humans in the loop requires mutual adaptati…