Tracailer: An Efficient Trajectory Planner for Tractor-Trailer Robots in Unstructured Environments

Fuente: arXiv
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Main Authors: Xu, Long, Chai, Kaixin, An, Boyuan, Gan, Jiaxiang, Ji, Shuhang, Hou, Zhenyu, Wang, Qianhao, Zhou, Yuan, Li, Xiaoying, Lin, Junxiao, Han, Zhichao, Xu, Chao, Cao, Yanjun, Gao, Fei
Format: Preprint
Published: 2025
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author Xu, Long
Chai, Kaixin
An, Boyuan
Gan, Jiaxiang
Ji, Shuhang
Hou, Zhenyu
Wang, Qianhao
Zhou, Yuan
Li, Xiaoying
Lin, Junxiao
Han, Zhichao
Xu, Chao
Cao, Yanjun
Gao, Fei
author_facet Xu, Long
Chai, Kaixin
An, Boyuan
Gan, Jiaxiang
Ji, Shuhang
Hou, Zhenyu
Wang, Qianhao
Zhou, Yuan
Li, Xiaoying
Lin, Junxiao
Han, Zhichao
Xu, Chao
Cao, Yanjun
Gao, Fei
contents The tractor-trailer robot consists of a drivable tractor and one or more non-drivable trailers connected via hitches. Compared to typical car-like robots, the addition of trailers provides greater transportation capability. However, this also complicates motion planning due to the robot's complex kinematics, high-dimensional state space, and deformable structure. To efficiently plan safe, time-optimal trajectories that adhere to the kinematic constraints of the robot and address the challenges posed by its unique features, this paper introduces a lightweight, compact, and high-order smooth trajectory representation for tractor-trailer robots. Based on it, we design an efficiently solvable spatial-temporal trajectory optimization problem. To deal with deformable structures, which leads to difficulties in collision avoidance, we fully leverage the collisionfree regions of the environment, directly applying deformations to trajectories in continuous space. This approach not requires constructing safe regions from the environment using convex approximations through collision-free seed points before each optimization, avoiding the loss of the solution space, thus reducing the dependency of the optimization on initial values. Moreover, a multi-terminal fast path search algorithm is proposed to generate the initial values for optimization. Extensive simulation experiments demonstrate that our approach achieves severalfold improvements in efficiency compared to existing algorithms, while also ensuring lower curvature and trajectory duration. Real-world experiments involving the transportation, loading and unloading of goods in both indoor and outdoor scenarios further validate the effectiveness of our method. The source code is accessible at https://github.com/Tracailer/Tracailer.
format Preprint
id arxiv_https___arxiv_org_abs_2502_19832
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Tracailer: An Efficient Trajectory Planner for Tractor-Trailer Robots in Unstructured Environments
Xu, Long
Chai, Kaixin
An, Boyuan
Gan, Jiaxiang
Ji, Shuhang
Hou, Zhenyu
Wang, Qianhao
Zhou, Yuan
Li, Xiaoying
Lin, Junxiao
Han, Zhichao
Xu, Chao
Cao, Yanjun
Gao, Fei
Robotics
The tractor-trailer robot consists of a drivable tractor and one or more non-drivable trailers connected via hitches. Compared to typical car-like robots, the addition of trailers provides greater transportation capability. However, this also complicates motion planning due to the robot's complex kinematics, high-dimensional state space, and deformable structure. To efficiently plan safe, time-optimal trajectories that adhere to the kinematic constraints of the robot and address the challenges posed by its unique features, this paper introduces a lightweight, compact, and high-order smooth trajectory representation for tractor-trailer robots. Based on it, we design an efficiently solvable spatial-temporal trajectory optimization problem. To deal with deformable structures, which leads to difficulties in collision avoidance, we fully leverage the collisionfree regions of the environment, directly applying deformations to trajectories in continuous space. This approach not requires constructing safe regions from the environment using convex approximations through collision-free seed points before each optimization, avoiding the loss of the solution space, thus reducing the dependency of the optimization on initial values. Moreover, a multi-terminal fast path search algorithm is proposed to generate the initial values for optimization. Extensive simulation experiments demonstrate that our approach achieves severalfold improvements in efficiency compared to existing algorithms, while also ensuring lower curvature and trajectory duration. Real-world experiments involving the transportation, loading and unloading of goods in both indoor and outdoor scenarios further validate the effectiveness of our method. The source code is accessible at https://github.com/Tracailer/Tracailer.
title Tracailer: An Efficient Trajectory Planner for Tractor-Trailer Robots in Unstructured Environments
topic Robotics
url https://arxiv.org/abs/2502.19832