Learning to Design and Construct Bridge without Blueprint
- URL: http://arxiv.org/abs/2108.02439v1
- Date: Thu, 5 Aug 2021 08:17:22 GMT
- Title: Learning to Design and Construct Bridge without Blueprint
- Authors: Yunfei Li, Tao Kong, Lei Li, Yifeng Li and Yi Wu
- Abstract summary: We study a new challenging assembly task, designing and constructing a bridge without a blueprint.
In this task, the robot needs to first design a feasible bridge architecture for arbitrarily wide cliffs and then manipulate the blocks reliably to construct a stable bridge according to the proposed design.
At the high level, the system learns a bridge blueprint policy in a physical simulator using deep reinforcement learning and curriculum learning.
For low-level control, we implement a motion-planning-based policy for real-robot motion control, which can be directly combined with a trained blueprint policy for real-world bridge construction without tuning.
- Score: 20.524052738716435
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Autonomous assembly has been a desired functionality of many intelligent
robot systems. We study a new challenging assembly task, designing and
constructing a bridge without a blueprint. In this task, the robot needs to
first design a feasible bridge architecture for arbitrarily wide cliffs and
then manipulate the blocks reliably to construct a stable bridge according to
the proposed design. In this paper, we propose a bi-level approach to tackle
this task. At the high level, the system learns a bridge blueprint policy in a
physical simulator using deep reinforcement learning and curriculum learning. A
policy is represented as an attention-based neural network with object-centric
input, which enables generalization to different numbers of blocks and cliff
widths. For low-level control, we implement a motion-planning-based policy for
real-robot motion control, which can be directly combined with a trained
blueprint policy for real-world bridge construction without tuning. In our
field study, our bi-level robot system demonstrates the capability of
manipulating blocks to construct a diverse set of bridges with different
architectures.
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