Non-Prehensile Manipulation in Clutter with Human-In-The-Loop

In this work, we propose a human-operator guided planning approach to pushing-based manipulation in clutter. We are interested in the problem where a robot needs to reach in clutter (for example on a shelf or in the fridge) to grasp a desired object. Obstacles might be blocking the way to that goal object, and the robot needs to decide which objects to push out of the way.

These reaching through clutter problems are difficult to solve due to several reasons: First, the number of objects make the state space of high-dimensionality because the planner needs to reason about the robot state and all the movable objects. Second, this is an under-actuated problem, since the objects cannot be controlled by the robot directly. Third, predicting the evolution of the system state requires running computationally expensive physics simulators, to predict how objects would move as a result of the robot pushing.

We build on kinodynamic planning approaches (like kinodynamic RRT and KPIECE), but we investigate using them in conjunction with human-operator input. In our framework, the human operator supplies a high-level plan to make the underlying planners solve the problem faster and with higher success rates.

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Citing

If you have any questions, please feel free to drop a line. Finally, if you want to cite this work, please use the following:

@inproceedings{papallas2020icra,
  title={Non-prehensile manipulation in clutter with human-in-the-loop},
  author={Papallas, Rafael and Dogar, Mehmet R},
  booktitle={2020 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={6723--6729},
  year={2020},
  organization={IEEE}
}