Time Distance: A Novel Collision Prediction and Path Planning Method

被引:1
作者
Analooee, Ali [1 ]
Azadi, Shahram [1 ]
Kazemi, Reza [1 ]
机构
[1] KN Toosi Univ Technol, Dept Mech Engn 1, Tehran 1991943344, Iran
来源
JOURNAL OF APPLIED AND COMPUTATIONAL MECHANICS | 2023年 / 9卷 / 03期
关键词
Automated vehicles; collision avoidance; mobile robots; motion planning; path planning; space-time space; MOTION; ALGORITHM; ROBOTS;
D O I
10.22055/jacm.2022.40688.3675
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
In this paper, a new fast algorithm for path planning and a collision prediction framework for two dimensional dynamically changing environments are introduced. The method is called Time Distance (TD) and benefits from the space-time space idea. First, the TD concept is defined as the time interval that must be spent in order for an object to reach another object or a location. Next, TD functions are derived as a function of location, velocity and geometry of objects. To construct the configuration-time space, TD functions in conjunction with another function named "Z-Infinity" are exploited. Finally, an explicit formula for creating the length optimal collision free path is presented. Length optimization in this formula is achieved using a function named "Route Function" which minimizes a cost function. Performance of the path planning algorithm is evaluated in simulations. Comparisons indicate that the algorithm is fast enough and capable to generate length optimal paths as the most effective methods do. Finally, as another usage of the TD functions, a collision prediction framework is presented. This framework consists of an explicit function which is a function of TD functions and calculates the TD of the vehicle with respect to all objects of the environment.
引用
收藏
页码:656 / 677
页数:22
相关论文
共 40 条
  • [1] Distributed multi-robot formation control in dynamic environments
    Alonso-Mora, Javier
    Montijano, Eduardo
    Nageli, Tobias
    Hilliges, Otmar
    Schwager, Mac
    Rus, Daniela
    [J]. AUTONOMOUS ROBOTS, 2019, 43 (05) : 1079 - 1100
  • [2] SCR-Normalize: A novel trajectory planning method based on explicit quintic polynomial curves
    Analooee, Ali
    Kazemi, Reza
    Azadi, Shahram
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART K-JOURNAL OF MULTI-BODY DYNAMICS, 2020, 234 (04) : 650 - 674
  • [3] [Anonymous], 1991, POSITIVE FEEDBACK SE
  • [4] [Anonymous], 1978, REP
  • [5] Atyabi Adham., 2013, International Journal of Advancements in Computing Technology, V5, P1
  • [6] Cadkhodajafarian A., 2018, MODARES MECH ENG, V17, P277
  • [7] A general framework for task-constrained motion planning with moving obstacles
    Cefalo, Massimo
    Oriolo, Giuseppe
    [J]. ROBOTICA, 2019, 37 (03) : 575 - 598
  • [8] Ant system: Optimization by a colony of cooperating agents
    Dorigo, M
    Maniezzo, V
    Colorni, A
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1996, 26 (01): : 29 - 41
  • [9] Dorigo M., 1992, OPTIMIZATION LEARNIN
  • [10] Sampling-Based Robot Motion Planning: A Review
    Elbanhawi, Mohamed
    Simic, Milan
    [J]. IEEE ACCESS, 2014, 2 : 56 - 77