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

2025-02-27

AI Summary

Motion planning for tractor-trailer systems in unstructured environments is challenging due to high-dimensional state spaces, complex kinematics, and variable articulated configurations. Method: This paper proposes a lightweight, high-order smooth spatiotemporal optimization framework. It employs high-order B-splines for trajectory parameterization; introduces a novel continuous-space deformation-based collision avoidance mechanism tailored to reconfigurable articulated structures—bypassing convex approximations that compromise solution space fidelity; and designs a multi-terminal heuristic path search algorithm to generate high-quality initial trajectories. Contribution/Results: The method achieves several-fold improvement in simulation efficiency over state-of-the-art approaches, while significantly reducing trajectory curvature and total execution time. It demonstrates robustness and practicality in both indoor and outdoor real-world cargo transportation tasks, validating its effectiveness for deployment in dynamic, unstructured environments.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search
• Intelligent Robots: Motion and Path Planning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

The tractor-trailer vehicle (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 spatio-temporal trajectory optimization problem. To deal with deformable structures, which leads to difficulties in collision avoidance, we fully leverage the collision-free 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 several-fold 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/ZJU-FAST-Lab/tracailer/.

Problem

• Efficient trajectory planning for tractor-trailer vehicles
• Addressing complex kinematics and high-dimensional state space
• Optimizing collision avoidance in unstructured environments

Innovation

• Lightweight trajectory representation for tractor-trailers
• Spatio-temporal trajectory optimization problem
• Multi-terminal fast path search algorithm