Robot Task Planning Under Local Observability
Max Merlin,Shane Parr,Neev Parikh,Sergio Orozco,Vedant Gupta,Eric Rosen,George Konidaris,Max Merlin,Shane Parr,Neev Parikh,Sergio Orozco,Vedant Gupta,Eric Rosen,George Konidaris
Real-world robot task planning is intractable in part due to partial observability. A common approach to reducing complexity is introducing additional structure into the decision process, such as mixed-observability, factored states, or temporally-extended actions. We propose the locally observable Markov decision process, a novel formulation that models task-level planning where uncertainty perta...
