How can we enable robots to efficiently reason both at discrete task-level and continuous motion-level to achieve high-level goals such as tidying up a room or constructing a building? This is a challenging problem that requires integrated reasoning about the combinatoric aspects, such as deciding which object to manipulate, and feasibility of each motion, such as collision-free constraints, to achieve goals. The classical robotics approach is to design a planner, that, given an initial state, goal, and transition model, computes a plan. The advantage of such a pure-planning approach is the immense generalization capability: for any given state and goal, the planner will find the solution if there is one...

• Motion planning
• Artificial Intelligence
• Mobile manipulation
• Combinatoric aspects
• Classical robotics

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