An Improved Model Predictive Trajectory Planning Method for Unmanned Tracked Vehicles on Undulating Terrains

Yinchu Zuo*, Chao Yang, Tianqi Qie, Weida Wang, Changle Xiang, Hongwei Wang

*Corresponding author for this work

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

Abstract

To ensure the safety and stability of unmanned tracked vehicles (UTV) driving under off-road scenarios, an improved model predictive trajectory planning method for UTV navigating on undulating terrains is proposed. Firstly, a terrain-based kinematic model is established to consider the impact of terrain features on the UTV attitude. Secondly, based on the model mentioned above, an improved model predictive trajectory planning (MPTP) method is proposed. This method can solve a trajectory that satisfies the motion constraints under undulating terrain scenarios. Thirdly, to reduce the computational complexity of the rolling optimization, an initial guess for MPTP is generated via a modified hybrid A∗ method, in which terrain features are considered. The proposed method has been validated in a typical undulating terrain scenario, and the results indicate that it performs better than conventional trajectory planning method for UTVs under the undulating terrain scenario.

Original languageEnglish
Title of host publicationProceedings of the 43rd Chinese Control Conference, CCC 2024
EditorsJing Na, Jian Sun
PublisherIEEE Computer Society
Pages6409-6414
Number of pages6
ISBN (Electronic)9789887581581
DOIs
Publication statusPublished - 2024
Event43rd Chinese Control Conference, CCC 2024 - Kunming, China
Duration: 28 Jul 202431 Jul 2024

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference43rd Chinese Control Conference, CCC 2024
Country/TerritoryChina
CityKunming
Period28/07/2431/07/24

Keywords

  • model predictive control
  • trajectory planning
  • undulating terrain
  • Unmanned tracked vehicle

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