Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Planning for the Unexpected: Explicitly Optimizing Motions for Ground
  Uncertainty in Running   We propose a method to generate actuation plans for a reduced order, dynamic
model of bipedal running. This method explicitly enforces robustness to ground
uncertainty. The plan generated is not a fixed body trajectory that is
aggressively stabilized: instead, the plan interacts with the passive dynamics
of the reduced order model to create emergent robustness. The goal is to create
plans for legged robots that will be robust to imperfect perception of the
environment, and to work with dynamics that are too complex to optimize in
real-time. Working within this dynamic model of legged locomotion, we optimize
a set of disturbance cases together with the nominal case, all with linked
inputs. The input linking is nontrivial due to the hybrid dynamics of the
running model but our solution is effective and has analytical gradients. The
optimization procedure proposed is significantly slower than a standard
trajectory optimization, but results in robust gaits that reject disturbances
extremely effectively without any replanning required.

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The categories of this paper are: atom-ph
19
The categories of this paper are: eess
3
The categories of this paper are: physics
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ