Fix/path smoothing robot radius (#1231)

* Fix: Include robot_radius in path_smoothing collision check

* Test: Add unit test to verify smoothed path respects robot_radius
This commit is contained in:
Shibo Liu
2025-06-21 07:04:57 +08:00
committed by GitHub
parent 194be251e1
commit 0e93ecb669
2 changed files with 136 additions and 23 deletions

View File

@@ -51,30 +51,93 @@ def get_target_point(path, targetL):
return [x, y, ti]
def line_collision_check(first, second, obstacleList):
# Line Equation
def is_point_collision(x, y, obstacle_list, robot_radius):
"""
Check whether a single point collides with any obstacle.
x1 = first[0]
y1 = first[1]
x2 = second[0]
y2 = second[1]
This function calculates the Euclidean distance between the given point (x, y)
and each obstacle center. If the distance is less than or equal to the sum of
the obstacle's radius and the robot's radius, a collision is detected.
try:
a = y2 - y1
b = -(x2 - x1)
c = y2 * (x2 - x1) - x2 * (y2 - y1)
except ZeroDivisionError:
return False
Args:
x (float): X-coordinate of the point to check.
y (float): Y-coordinate of the point to check.
obstacle_list (List[Tuple[float, float, float]]): List of obstacles defined as (ox, oy, radius).
robot_radius (float): Radius of the robot, used to inflate the obstacles.
for (ox, oy, size) in obstacleList:
d = abs(a * ox + b * oy + c) / (math.hypot(a, b))
if d <= size:
return False
return True # OK
Returns:
bool: True if the point is in collision with any obstacle, False otherwise.
"""
for (ox, oy, obstacle_radius) in obstacle_list:
d = math.hypot(ox - x, oy - y)
if d <= obstacle_radius + robot_radius:
return True # Collided
return False
def path_smoothing(path, max_iter, obstacle_list):
def line_collision_check(first, second, obstacle_list, robot_radius=0.0, sample_step=0.2):
"""
Check if the line segment between `first` and `second` collides with any obstacle.
Considers the robot_radius by inflating the obstacle size.
Args:
first (List[float]): Start point of the line [x, y]
second (List[float]): End point of the line [x, y]
obstacle_list (List[Tuple[float, float, float]]): Obstacles as (x, y, radius)
robot_radius (float): Radius of robot
sample_step (float): Distance between sampling points along the segment
Returns:
bool: True if collision-free, False otherwise
"""
x1, y1 = first[0], first[1]
x2, y2 = second[0], second[1]
dx = x2 - x1
dy = y2 - y1
length = math.hypot(dx, dy)
if length == 0:
# Degenerate case: point collision check
return not is_point_collision(x1, y1, obstacle_list, robot_radius)
steps = int(length / sample_step) + 1 # Sampling every sample_step along the segment
for i in range(steps + 1):
t = i / steps
x = x1 + t * dx
y = y1 + t * dy
if is_point_collision(x, y, obstacle_list, robot_radius):
return False # Collision found
return True # Safe
def path_smoothing(path, max_iter, obstacle_list, robot_radius=0.0):
"""
Smooths a given path by iteratively replacing segments with shortcut connections,
while ensuring the new segments are collision-free.
The algorithm randomly picks two points along the original path and attempts to
connect them with a straight line. If the line does not collide with any obstacles
(considering the robot's radius), the intermediate path points between them are
replaced with the direct connection.
Args:
path (List[List[float]]): The original path as a list of [x, y] coordinates.
max_iter (int): Number of iterations for smoothing attempts.
obstacle_list (List[Tuple[float, float, float]]): List of obstacles represented as
(x, y, radius).
robot_radius (float, optional): Radius of the robot, used to inflate obstacle size
during collision checking. Defaults to 0.0.
Returns:
List[List[float]]: The smoothed path as a list of [x, y] coordinates.
Example:
>>> smoothed = path_smoothing(path, 1000, obstacle_list, robot_radius=0.5)
"""
le = get_path_length(path)
for i in range(max_iter):
@@ -94,7 +157,7 @@ def path_smoothing(path, max_iter, obstacle_list):
continue
# collision check
if not line_collision_check(first, second, obstacle_list):
if not line_collision_check(first, second, obstacle_list, robot_radius):
continue
# Create New path
@@ -119,14 +182,16 @@ def main():
(3, 10, 2),
(7, 5, 2),
(9, 5, 2)
] # [x,y,size]
] # [x,y,radius]
rrt = RRT(start=[0, 0], goal=[6, 10],
rand_area=[-2, 15], obstacle_list=obstacleList)
rand_area=[-2, 15], obstacle_list=obstacleList,
robot_radius=0.3)
path = rrt.planning(animation=show_animation)
# Path smoothing
maxIter = 1000
smoothedPath = path_smoothing(path, maxIter, obstacleList)
smoothedPath = path_smoothing(path, maxIter, obstacleList,
robot_radius=rrt.robot_radius)
# Draw final path
if show_animation: