mirror of
https://github.com/AtsushiSakai/PythonRobotics.git
synced 2026-01-14 00:27:55 -05:00
146 lines
3.2 KiB
Python
146 lines
3.2 KiB
Python
"""
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Path planning Sample Code with RRT with path smoothing
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@author: AtsushiSakai(@Atsushi_twi)
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"""
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import math
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import random
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import matplotlib.pyplot as plt
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import sys
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import pathlib
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sys.path.append(str(pathlib.Path(__file__).parent))
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from rrt import RRT
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show_animation = True
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def get_path_length(path):
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le = 0
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for i in range(len(path) - 1):
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dx = path[i + 1][0] - path[i][0]
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dy = path[i + 1][1] - path[i][1]
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d = math.hypot(dx, dy)
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le += d
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return le
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def get_target_point(path, targetL):
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le = 0
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ti = 0
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lastPairLen = 0
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for i in range(len(path) - 1):
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dx = path[i + 1][0] - path[i][0]
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dy = path[i + 1][1] - path[i][1]
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d = math.hypot(dx, dy)
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le += d
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if le >= targetL:
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ti = i - 1
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lastPairLen = d
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break
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partRatio = (le - targetL) / lastPairLen
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x = path[ti][0] + (path[ti + 1][0] - path[ti][0]) * partRatio
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y = path[ti][1] + (path[ti + 1][1] - path[ti][1]) * partRatio
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return [x, y, ti]
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def line_collision_check(first, second, obstacleList):
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# Line Equation
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x1 = first[0]
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y1 = first[1]
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x2 = second[0]
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y2 = second[1]
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try:
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a = y2 - y1
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b = -(x2 - x1)
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c = y2 * (x2 - x1) - x2 * (y2 - y1)
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except ZeroDivisionError:
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return False
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for (ox, oy, size) in obstacleList:
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d = abs(a * ox + b * oy + c) / (math.hypot(a, b))
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if d <= size:
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return False
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return True # OK
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def path_smoothing(path, max_iter, obstacle_list):
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le = get_path_length(path)
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for i in range(max_iter):
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# Sample two points
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pickPoints = [random.uniform(0, le), random.uniform(0, le)]
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pickPoints.sort()
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first = get_target_point(path, pickPoints[0])
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second = get_target_point(path, pickPoints[1])
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if first[2] <= 0 or second[2] <= 0:
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continue
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if (second[2] + 1) > len(path):
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continue
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if second[2] == first[2]:
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continue
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# collision check
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if not line_collision_check(first, second, obstacle_list):
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continue
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# Create New path
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newPath = []
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newPath.extend(path[:first[2] + 1])
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newPath.append([first[0], first[1]])
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newPath.append([second[0], second[1]])
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newPath.extend(path[second[2] + 1:])
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path = newPath
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le = get_path_length(path)
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return path
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def main():
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# ====Search Path with RRT====
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# Parameter
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obstacleList = [
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(5, 5, 1),
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(3, 6, 2),
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(3, 8, 2),
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(3, 10, 2),
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(7, 5, 2),
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(9, 5, 2)
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] # [x,y,size]
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rrt = RRT(start=[0, 0], goal=[6, 10],
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rand_area=[-2, 15], obstacle_list=obstacleList)
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path = rrt.planning(animation=show_animation)
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# Path smoothing
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maxIter = 1000
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smoothedPath = path_smoothing(path, maxIter, obstacleList)
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# Draw final path
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if show_animation:
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rrt.draw_graph()
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plt.plot([x for (x, y) in path], [y for (x, y) in path], '-r')
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plt.plot([x for (x, y) in smoothedPath], [
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y for (x, y) in smoothedPath], '-c')
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plt.grid(True)
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plt.pause(0.01) # Need for Mac
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plt.show()
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if __name__ == '__main__':
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main()
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