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Motion Planning
While driving a car, we do not have unambiguous rules or equations to follow; everyday driving is an inexact science.
However, a car-like robot that drives itself must have exact motion-planning algorithms. We have to give a distinct algorithm for each given situation and requirements. MotionLab has succeeded in it, as you can see video demonstrations in this website. For instance, the motion-planning algorithms of Maze and Parallel Parking are totally different.
Furthermore, MotionLab has discovered a complete mathematical model on designing motion-planning algorithms; ALL the algorithms can be composed of only four kinds of atomic motion-control methods.
  • We have discovered that any car-like vehicle’s motions can be composed of the following four motion-control methods: (1) Curvature-Based Method, (2) Direction-Based Method, (3) Line-Based Method, and (4) Omega-Based Method.
  • All the methods are independent each other: each method cannot emulate any another.
  •  A motion may be composed of a multiple number of these atomic methods.
The new math, Symmetric Geometry, has led us to this result. The use of the  motion-control methods embody precise, safe, stable, and gentle Swan motions, as you can see. This mathematical model is hardware independent.
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