Time Distance: A Novel Collision Prediction and Path Planning Method
Ali Analooee, Shahram Azadi, Reza Kazemi

TL;DR
This paper introduces Time Distance, a fast path planning and collision prediction method in dynamic environments, utilizing space-time concepts to generate length optimal collision-free paths efficiently.
Contribution
The paper presents the novel Time Distance (TD) algorithm and a collision prediction framework that leverage space-time space ideas for improved path planning in dynamic settings.
Findings
The TD-based algorithm is fast and capable of generating length optimal paths.
Simulation results show the method outperforms existing approaches in speed and optimality.
The collision prediction framework accurately calculates collision times using TD functions.
Abstract
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…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Autonomous Vehicle Technology and Safety · Control and Dynamics of Mobile Robots
