Real-world multi-objective engineering design optimization problems often have parameters with uncontrollable variations. The aim of solving such problems is to obtain solutions t...
We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
Real-time search methods are suited for tasks in which the agent is interacting with an initially unknown environment in real time. In such simultaneous planning and learning prob...
— We present a sampling-based path planning and replanning algorithm that produces anytime solutions. Our algorithm tunes the quality of its result based on available search time...
In this paper we present an approach to obstacle avoidance and local path planning for polygonal robots. It decomposes the task into a model stage and a planning stage. The model ...
Kai Oliver Arras, Jan Persson, Nicola Tomatis, Rol...