3 accepted papers
Constraint-based robot programming allows for implementing sensor-based skills that react to disturbances on the one hand, and composable skills that dynamically create and reconfigure complex robot behaviors on the other hand. In this letter, we address a class of problems where composing appropria
Experience-based planning domains (EBPDs) have been proposed to improve problem solving by learning from experience. They rely on acquiring and using task knowledge, i.e., activity schemata, for generating solutions to problem instances in a class of tasks. Using Three-Valued Logic Analysis (TVLA),…
This paper addresses robot task model learning and planning with loops. By detecting and modeling loops in solved tasks it is possible to learn and solve wider classes of problems. We extend our previous work on experience-based planning domains in robotics to detect, represent and generate loops in…