Temporal Concurrent Planning with Stressed Actions

Temporal stress is something that humans have to face nearly every day. Humans have to handle situations, where there is not much time left for a specific task. Most robotic systems, on the other hand, are not able to act in such temporally unstructured environments. For that reason, we present the novel Temporal Stressing Fast Downward (TSFD)planning system based on Temporal Fast Downward (TFD), which solves temporal problems using a modified heuristic forward search. With this planner, we introduce the novel concept of stressed actions for temporally bounded problems. Stressed actions enable a robot to accelerate or decelerate actions under consideration of an action-specific temporal cost function and the available time for plan execution. We further introduce an improved decision epoch search that allows complete planning with temporal gaps. Our evaluation in benchmark domains and on the real humanoid robot ARMAR-III shows that TSFD has the ability to produce plans of better makespan than TFD and is able to solve problems that could not be handled before. Furthermore, TSFD performs better in typical service robotics tasks than baseline approaches. Finally, we show that stressed actions greatly increase the possibility of finding feasible solutions in temporally bounded tasks.