The automation of processes, especially in the automotive sector, has experienced an increase in safety and efficiency, and at the same time, it reduces execution times and human errors. Nowadays, conventional logistics has experimented with significant change. Those go from individual transport services using personal vehicles, passing through internal logistics of the warehouse, and finishing with the delivery of goods in different last mile transport and circumstances with mobile robots (e.g. Amazon logistic centers). However, the automation solutions for heavy-duty vehicles during loading and unloading processes are still a research challenge. This work presents a trajectory planning which targets automated semi-trailer trucks. The algorithm considers turning under difficult and tight circumstances, as well as reversing maneuvers. It is based on RRT (Rapidly exploring Random Trees) planning. The validation was done in a simulation environment considering a logistic warehouse. The solution generates the best possible path in a short time (under 500 milliseconds), and it is a promising result for a near-future real-deployment.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    RRT Trajectory Planning Approach For Automated Semi-trailer truck Parking


    Contributors:


    Publication date :

    2022-11-14


    Size :

    4401066 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Research on Parking Control of Semi-trailer Truck

    Li, Zhiqiang / Cheng, Hao / Ma, Jiajun et al. | IEEE | 2020



    Autonomous Truck-Trailer Maneuvering and Parking

    RAMIREZ LLANOS EDUARDO JOSE / VERMA DHIREN / YU XIN et al. | European Patent Office | 2022

    Free access

    Semi-trailer, trailer truck and method for braking a semi-trailer

    DREWES OLAF | European Patent Office | 2020

    Free access

    Autonomous truck-trailer maneuvering and parking

    RAMIREZ LLANOS EDUARDO JOSE / VERMA DHIREN / YU XIN et al. | European Patent Office | 2024

    Free access