Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning Collision-free and Torque-limited Robot Trajectories based on
  Alternative Safe Behaviors   This paper presents an approach to learn online generation of collision-free
and torque-limited robot trajectories. In order to generate future motions, a
neural network is periodically invoked. Based on the current kinematic state of
the robot and the network prediction, a trajectory for the current time
interval can be calculated. The main idea of our paper is to execute the
predicted motion only if a collision-free and torque-limited way to continue
the trajectory is known. In practice, the motion predicted for the current time
interval is extended by a braking trajectory and simulated using a physics
engine. If the simulated trajectory complies with all safety constraints, the
predicted motion is carried out. Otherwise, the braking trajectory calculated
in the previous time interval serves as an alternative safe behavior. Given a
task-specific reward function, the neural network is trained using
reinforcement learning. The design of the action space used for reinforcement
learning ensures that all predicted trajectories comply with kinematic joint
limits. For our evaluation, simulated industrial robots and humanoid robots are
trained to reach as many randomly placed target points as possible. We show
that our method reliably prevents collisions with static obstacles and
collisions between the robot arms, while generating motions that respect both
torque limits and kinematic joint limits. Experiments with a real robot
demonstrate that safe trajectories can be generated in real-time.

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The categories of this paper are: physics
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The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
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The categories of this paper are: quant-ph
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The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol
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The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
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The categories of this paper are: gr-qc
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The categories of this paper are: hep-th
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The categories of this paper are: hep-ex
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The categories of this paper are: acc-phys
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The categories of this paper are: cmp-lg
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The categories of this paper are: cond-mat
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The categories of this paper are: q-alg