tBurton: A Divide and Conquer Temporal Planner
Planning for and controlling a network of interacting devices requires a planner that accounts for the automatic timed transitions of devices while meeting deadlines and achieving durative goals. For example, a planner for an imaging satellite with a camera intolerant of exhaust would need to determine that opening a valve causes a chain reaction that ignites the engine, and thus needs to shield its camera. While planners exist that support deadlines and durative goals, currently, no planners can handle automatic timed transitions. We present tBurton, a temporal planner that supports these features while additionally producing a temporally least-commitment plan. tBurton uses a divide and conquer approach: dividing the problem using causal-graph decomposition and conquering each factor with heuristic forward search. The `sub-plans' from each factor are unified in a conflict directed search, guided by the causal graph structure. We describe why tBurton is fast and efficient and present its efficacy on benchmarks from the International Planning Competition.
