Dixit, Anushri and Lindemann, Lars and Wei, Skylar X. and Cleaveland, Matthew and Pappas, George J. and Burdick, Joel W. (2022) Adaptive Conformal Prediction for Motion Planning among Dynamic Agents. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20221219-234025206
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Abstract
This paper proposes an algorithm for motion planning among dynamic agents using adaptive conformal prediction. We consider a deterministic control system and use trajectory predictors to predict the dynamic agents' future motion, which is assumed to follow an unknown distribution. We then leverage ideas from adaptive conformal prediction to dynamically quantify prediction uncertainty from an online data stream. Particularly, we provide an online algorithm uses delayed agent observations to obtain uncertainty sets for multistep-ahead predictions with probabilistic coverage. These uncertainty sets are used within a model predictive controller to safely navigate among dynamic agents. While most existing data-driven prediction approached quantify prediction uncertainty heuristically, we quantify the true prediction uncertainty in a distribution-free, adaptive manner that even allows to capture changes in prediction quality and the agents' motion. We empirically evaluate of our algorithm on a simulation case studies where a drone avoids a flying frisbee.
Item Type: | Report or Paper (Discussion Paper) | ||||||||||||
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Additional Information: | © 2023 A. Dixit, L. Lindemann, S.X. Wei, M. Cleaveland, G.J. Pappas & J.W. Burdick. Attribution 4.0 International (CC BY 4.0). Lars Lindemann, Matthew Cleaveland, and George J. Pappas were generously supported by NSF award CPS-2038873. The work of Anushri Dixit and Skylar Wei was supported in part by DARPA, through the LINC program. | ||||||||||||
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Record Number: | CaltechAUTHORS:20221219-234025206 | ||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20221219-234025206 | ||||||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||
ID Code: | 118457 | ||||||||||||
Collection: | CaltechAUTHORS | ||||||||||||
Deposited By: | George Porter | ||||||||||||
Deposited On: | 20 Dec 2022 03:39 | ||||||||||||
Last Modified: | 20 Dec 2022 03:39 |
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