Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Inverse Optimal Control from Incomplete Trajectory Observations   This article develops a methodology that enables learning an objective
function of an optimal control system from incomplete trajectory observations.
The objective function is assumed to be a weighted sum of features (or basis
functions) with unknown weights, and the observed data is a segment of a
trajectory of system states and inputs. The proposed technique introduces the
concept of the recovery matrix to establish the relationship between any
available segment of the trajectory and the weights of given candidate
features. The rank of the recovery matrix indicates whether a subset of
relevant features can be found among the candidate features and the
corresponding weights can be learned from the segment data. The recovery matrix
can be obtained iteratively and its rank non-decreasing property shows that
additional observations may contribute to the objective learning. Based on the
recovery matrix, a method for using incomplete trajectory observations to learn
the weights of selected features is established, and an incremental inverse
optimal control algorithm is developed by automatically finding the minimal
required observation. The effectiveness of the proposed method is demonstrated
on a linear quadratic regulator system and a simulated robot manipulator.

15
The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
3
The categories of this paper are: physics
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
9
The categories of this paper are: nlin
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph