Mobile robot path planning method based on multi-barrier environment
A mobile robot and path planning technology, applied in the field of mobile robots, can solve problems such as robot path deviation and inconvenient laying methods, and achieve the effect of improving construction efficiency
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Embodiment 1
[0089] Example 1: Path optimization with weight initial values tending towards safety.
[0090] like Figure 8 As shown, the optimal path of the robot in this embodiment is more inclined to safety, see the initial values of the two types of coefficients. Figure 8 The three points in are all points below the safety factor threshold; the distance between the two QR code points A and C is less than the minimum recognition distance D of the robot. Before the path optimization, although the AC path is the shortest path intuitively, However, after recalculation by assigning weight coefficients and weights, the final optimized path result is: AB+BC. The principle and calculation method of the robot path optimization method in this embodiment are as follows:
[0091] (1) Set the starting point A and the target point C;
[0092] (2) Points A and C are two-dimensional code points; point B is the link point of the link diagram;
[0093] (3) The first coefficient of each point is...
Embodiment 2
[0100] Embodiment 2: The initial value of the weight tends to be a robot path optimization method in which the safety factor is equal and the attribute coefficients of the points are equal.
[0101] like Figure 9 As shown in the figure, the optimized path of the robot in this embodiment is more inclined to have equal safety coefficients and equal attribute coefficients of points. The principle and calculation method of the robot path optimization method are as follows:
[0102] ⑴Because Figure 9 The QR codes with low security attributes have been filtered out in the QR code, and all the remaining mixed points can be regarded as equal safety factors, that is, the link points of the link map and the QR code points have the same safety factor.
[0103] (2) Assume that the distance from point ① to point ② is less than the minimum distance D that the robot can recognize;
[0104] (3) Since the attribute coefficients of points ② and ④ are the same; the attribute coefficients of ...
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