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Risk-Aware Path Planning Using CVaR for Quadrotors

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the presence of obstacles with static position uncertainty, a risk-aware path planning method using the conditional value-at-risk (CVaR) is proposed. Given the current position of the quadrotor, CVaR can effectively quantify the risk of collision with the static uncertain obstacle whose center of mass (CoM) follows a joint normal distribution. As a specific application of CVaR, the CVaR constrained A∗(CVaR-A∗ for simplicity) algorithm is designed to search for the optimal path while ensuring the safety of the quadrotor. The simulation results are presented to indicate the feasibility and effectiveness of the proposed CVaR-A∗ algorithm.

Original languageEnglish
Title of host publication2023 6th International Symposium on Autonomous Systems, ISAS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350316155
DOIs
StatePublished - 2023
Event6th International Symposium on Autonomous Systems, ISAS 2023 - Nanjing, China
Duration: 23 Jun 202325 Jun 2023

Publication series

Name2023 6th International Symposium on Autonomous Systems, ISAS 2023

Conference

Conference6th International Symposium on Autonomous Systems, ISAS 2023
Country/TerritoryChina
CityNanjing
Period23/06/2325/06/23

Keywords

  • CVaR-A∗
  • path planning
  • risk-aware
  • static position uncertainty

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