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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. https://resolver.caltech.edu/CaltechAUTHORS:20210119-161649869

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Abstract

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
Related URLs:
URLURL TypeDescription
https://doi.org/10.23919/ECC54610.2021.9655104DOIArticle
https://arxiv.org/abs/2011.11211arXivDiscussion Paper
ORCID:
AuthorORCID
Ahmadi, Mohamadreza0000-0003-1447-3012
Additional Information:© 2021 EUCA.
DOI:10.23919/ECC54610.2021.9655104
Record Number:CaltechAUTHORS:20210119-161649869
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210119-161649869
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
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:20 Jan 2021 15:07
Last Modified:11 Apr 2022 16:46

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