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Risk-Sensitive Motion Planning using Entropic Value-at-Risk

Dixit, Anushri and Ahmadi, Mohamadreza and Burdick, Joel W. (2021) Risk-Sensitive Motion Planning using Entropic Value-at-Risk. In: 2021 European Control Conference (ECC). IEEE , Piscataway, NJ, pp. 1726-1732. ISBN 978-9-4638-4236-5.

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We consider the problem of risk-sensitive motion planning in the presence of randomly moving obstacles. To this end, we adopt a model predictive control (MPC) scheme and pose the obstacle avoidance constraint in the MPC problem as a distributionally robust constraint with a KL divergence ambiguity set. This constraint is the dual representation of the Entropic Value-at-Risk (EVaR). Building upon this viewpoint, we propose an algorithm to follow waypoints and discuss its feasibility and completion in finite time. We compare the policies obtained using EVaR with those obtained using another common coherent risk measure, Conditional Value-at-Risk (CVaR), via numerical experiments for a 2D system. We also implement the waypoint following algorithm on a 3D quadcopter simulation.

Item Type:Book Section
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Ahmadi, Mohamadreza0000-0003-1447-3012
Additional Information:© 2021 EUCA.
Record Number:CaltechAUTHORS:20210119-161649869
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Official Citation:A. Dixit, M. Ahmadi and J. W. Burdick, "Risk-Sensitive Motion Planning using Entropic Value-at-Risk," 2021 European Control Conference (ECC), 2021, pp. 1726-1732, doi: 10.23919/ECC54610.2021.9655104
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107576
Deposited By: George Porter
Deposited On:20 Jan 2021 15:07
Last Modified:11 Apr 2022 16:46

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