This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis ...

This thesis is set within the context of the problem of motion planning in autonomous driving. Due to nonlinear system dynamics and non-convex constraints, this problem is challenging even under simplifying assumptions (e.g. non-cooperating traffic participants obey traffic rules, lossless inter-vehicle communication, absence of measuring errors). Typical solution approaches rely on a decomposition of the problem into subproblems which are easier to solve. This decomposition often results in a hierarchy of subproblems ...