matssteinweg
parent
76df3ce814
commit
e87596d5e8
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@ -24,7 +24,20 @@ class Waypoint:
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self.psi = psi
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self.kappa = kappa
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# information about drivable area at waypoint
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# upper and lower bound of drivable area orthogonal to
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# waypoint orientation
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self.lb = None
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self.ub = None
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self.border_cells = None
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def __sub__(self, other):
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"""
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Overload subtract operator. Difference of two waypoints is equal to
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their euclidean distance.
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:param other: subtrahend
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:return: euclidean distance between two waypoints
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"""
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return ((self.x - other.x)**2 + (self.y - other.y)**2)**0.5
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@ -34,35 +47,46 @@ class Waypoint:
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class ReferencePath:
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def __init__(self, map, wp_x, wp_y, resolution, smoothing_distance, width_info=False):
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def __init__(self, map, wp_x, wp_y, resolution, smoothing_distance, max_width):
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"""
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Reference Path object. Create a reference trajectory from specified
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corner points with given resolution. Smoothing around corners can be
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applied.
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applied. Waypoints represent center-line of the path with specified
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maximum width to both sides.
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:param map: map object on which path will be placed
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:param wp_x: x coordinates of corner points in global coordinates
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:param wp_y: y coordinates of corner points in global coordinates
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:param resolution: resolution of the path in m/wp
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:param smoothing_distance: number of waypoints used for smoothing the
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path by averaging neighborhood of waypoints
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:param max_width: maximum width of path to both sides in m
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"""
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# precision
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# Precision
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self.eps = 1e-12
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# map
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# Map
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self.map = map
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# resolution of the path
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# Resolution of the path
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self.resolution = resolution
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# look ahead distance for path averaging
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# Look ahead distance for path averaging
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self.smoothing_distance = smoothing_distance
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# waypoints with x, y, psi, k
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self.waypoints = self.construct_path(wp_x, wp_y)
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# List of waypoint objects
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self.waypoints = self._construct_path(wp_x, wp_y)
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# path width
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self.get_width_info = width_info
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if self.get_width_info:
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self.width_info = self.compute_width()
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self.min_width = (np.min(self.width_info[0, :]),
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np.min(self.width_info[3, :]))
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# Compute path width (attribute of each waypoint)
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self._compute_width(max_width=max_width)
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def construct_path(self, wp_x, wp_y):
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def _construct_path(self, wp_x, wp_y):
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"""
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Construct path from given waypoints.
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:param wp_x: x coordinates of waypoints in global coordinates
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:param wp_y: y coordinates of waypoints in global coordinates
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:return: list of waypoint objects
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"""
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# Number of waypoints
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n_wp = [int(np.sqrt((wp_x[i + 1] - wp_x[i]) ** 2 +
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@ -78,7 +102,7 @@ class ReferencePath:
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tolist() for i in range(len(wp_y) - 1)]
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wp_y = [wp for segment in wp_y for wp in segment] + [gp_y]
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# smooth path
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# Smooth path
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wp_xs = []
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wp_ys = []
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for wp_id in range(self.smoothing_distance, len(wp_x) -
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@ -88,147 +112,282 @@ class ReferencePath:
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wp_ys.append(np.mean(wp_y[wp_id - self.smoothing_distance:wp_id
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+ self.smoothing_distance + 1]))
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# Construct list of waypoint objects
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waypoints = list(zip(wp_xs, wp_ys))
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waypoints = self.spatial_reformulation(waypoints)
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waypoints = self._construct_waypoints(waypoints)
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return waypoints
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def spatial_reformulation(self, waypoints):
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def _construct_waypoints(self, waypoint_coordinates):
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"""
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Reformulate conventional waypoints (x, y) coordinates into waypoint
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objects containing (x, y, psi, kappa)
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objects containing (x, y, psi, kappa, ub, lb)
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:param waypoint_coordinates: list of (x, y) coordinates of waypoints in
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global coordinates
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:return: list of waypoint objects for entire reference path
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"""
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waypoints_spatial = []
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for wp_id in range(len(waypoints) - 1):
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# List containing waypoint objects
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waypoints = []
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# get start and goal waypoints
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current_wp = np.array(waypoints[wp_id])
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next_wp = np.array(waypoints[wp_id + 1])
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# Iterate over all waypoints
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for wp_id in range(len(waypoint_coordinates) - 1):
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# difference vector
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# Get start and goal waypoints
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current_wp = np.array(waypoint_coordinates[wp_id])
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next_wp = np.array(waypoint_coordinates[wp_id + 1])
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# Difference vector
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dif_ahead = next_wp - current_wp
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# angle ahead
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# Angle ahead
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psi = np.arctan2(dif_ahead[1], dif_ahead[0])
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# distance to next waypoint
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# Distance to next waypoint
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dist_ahead = np.linalg.norm(dif_ahead, 2)
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# get x and y coordinates of current waypoint
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x = current_wp[0]
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y = current_wp[1]
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# Get x and y coordinates of current waypoint
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x, y = current_wp[0], current_wp[1]
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# Compute local curvature at waypoint
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# first waypoint
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if wp_id == 0:
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kappa = 0
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else:
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prev_wp = np.array(waypoints[wp_id - 1])
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prev_wp = np.array(waypoint_coordinates[wp_id - 1])
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dif_behind = current_wp - prev_wp
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angle_behind = np.arctan2(dif_behind[1], dif_behind[0])
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angle_dif = np.mod(psi - angle_behind + math.pi, 2 * math.pi) \
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- math.pi
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kappa = np.abs(angle_dif / (dist_ahead + self.eps))
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kappa = angle_dif / (dist_ahead + self.eps)
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waypoints_spatial.append(Waypoint(x, y, psi, kappa))
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waypoints.append(Waypoint(x, y, psi, kappa))
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return waypoints_spatial
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return waypoints
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def compute_width(self, max_dist=2.0):
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max_dist = max_dist # m
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width_info = np.zeros((6, len(self.waypoints)))
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def _compute_width(self, max_width):
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"""
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Compute the width of the path by checking the maximum free space to
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the left and right of the center-line.
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:param max_width: maximum width of the path.
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"""
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# Iterate over all waypoints
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for wp_id, wp in enumerate(self.waypoints):
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# List containing information for current waypoint
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width_info = []
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# Check width left and right of the center-line
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for i, dir in enumerate(['left', 'right']):
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# get pixel coordinates of waypoint
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wp_x, wp_y = self.map.w2m(wp.x, wp.y)
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# get angle orthogonal to path in current direction
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# Get angle orthogonal to path in current direction
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if dir == 'left':
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angle = np.mod(wp.psi + math.pi / 2 + math.pi,
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2 * math.pi) - math.pi
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else:
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angle = np.mod(wp.psi - math.pi / 2 + math.pi,
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2 * math.pi) - math.pi
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# get closest cell to orthogonal vector
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t_x, t_y = self.map.w2m(wp.x + max_dist * np.cos(angle), wp.y + max_dist * np.sin(angle))
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# compute path between cells
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width_info[3*i:3*(i+1), wp_id] = self.get_min_dist(wp_x, wp_y, t_x, t_y, max_dist)
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return width_info
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# Get closest cell to orthogonal vector
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t_x, t_y = self.map.w2m(wp.x + max_width * np.cos(angle), wp.y
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+ max_width * np.sin(angle))
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# Compute distance to orthogonal cell on path border
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b_value, b_cell = self._get_min_width(wp, t_x, t_y, max_width)
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# Add information to list for current waypoint
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width_info.append(b_value)
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width_info.append(b_cell)
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def get_min_dist(self, wp_x, wp_y, t_x, t_y, max_dist):
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# get neighboring cells (account for discretization)
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neighbors_x, neighbors_y = [], []
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# Set waypoint attributes with width to the left and right
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wp.ub = width_info[0]
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wp.lb = -1 * width_info[2] # minus can be assumed as waypoints
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# represent center-line of the path
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# Set border cells of waypoint
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wp.border_cells = (width_info[1], width_info[3])
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def _get_min_width(self, wp, t_x, t_y, max_width):
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"""
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Compute the minimum distance between the current waypoint and the
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orthogonal cell on the border of the path
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:param wp: current waypoint
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:param t_x: x coordinate of border cell in map coordinates
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:param t_y: y coordinate of border cell in map coordinates
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:param max_width: maximum path width in m
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:return: min_width to border and corresponding cell
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"""
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# Get neighboring cells of orthogonal cell (account for
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# discretization inaccuracy)
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tn_x, tn_y = [], []
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for i in range(-1, 2, 1):
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for j in range(-1, 2, 1):
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neighbors_x.append(t_x + i)
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neighbors_y.append(t_y + j)
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tn_x.append(t_x+i)
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tn_y.append(t_y+j)
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# get bresenham paths to all neighboring cells
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# Get pixel coordinates of waypoint
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wp_x, wp_y = self.map.w2m(wp.x, wp.y)
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# Get Bresenham paths to all possible cells
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paths = []
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for t_x, t_y in zip(neighbors_x, neighbors_y):
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for t_x, t_y in zip(tn_x, tn_y):
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path = list(bresenham(wp_x, wp_y, t_x, t_y))
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paths.append(path)
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min_dist = max_dist
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# Compute minimum distance to border cell
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min_width = max_width
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# map inspected cell to world coordinates
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min_cell = self.map.m2w(t_x, t_y)
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for path in paths:
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for cell in path:
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t_x = cell[0]
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t_y = cell[1]
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# if path goes through occupied cell
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t_x, t_y = cell[0], cell[1]
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# If path goes through occupied cell
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if self.map.data[t_y, t_x] == 0:
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# get world coordinates
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x, y = self.map.m2w(wp_x, wp_y)
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# Get world coordinates
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c_x, c_y = self.map.m2w(t_x, t_y)
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cell_dist = np.sqrt((x - c_x) ** 2 + (y - c_y) ** 2)
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if cell_dist < min_dist:
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min_dist = cell_dist
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cell_dist = np.sqrt((wp.x - c_x) ** 2 + (wp.y - c_y) ** 2)
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if cell_dist < min_width:
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min_width = cell_dist
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min_cell = (c_x, c_y)
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dist_info = np.array([min_dist, min_cell[0], min_cell[1]])
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return dist_info
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def show(self):
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# decrease min_width by radius of circle around cell
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min_width -= 1 / np.sqrt(2) * self.map.resolution
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# plot map
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return min_width, min_cell
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def update_bounds(self, wp_id):
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"""
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Compute upper and lower bounds of the drivable area orthogonal to
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the given waypoint.
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:param wp_id: ID of reference waypoint
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"""
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# Get reference waypoint
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wp = self.waypoints[wp_id]
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# Get waypoint's border cells in map coordinates
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ub_p = self.map.w2m(wp.border_cells[0][0], wp.border_cells[0][1])
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lb_p = self.map.w2m(wp.border_cells[1][0], wp.border_cells[1][1])
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# Compute path from left border cell to right border cell
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path = list(bresenham(ub_p[0], ub_p[1], lb_p[0], lb_p[1]))
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# Initialize upper and lower bound of drivable area to
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# upper bound of path
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ub_o, lb_o = ub_p, ub_p
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# Initialize upper and lower bound of best segment to upper bound of
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# path
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ub_ls, lb_ls = ub_p, ub_p
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# Iterate over path from left border to right border
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for x, y in path:
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# If cell is free, update lower bound
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if self.map.data[y, x] == 1:
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lb_o = (x, y)
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# If cell is occupied, end segment. Update best segment if current
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# segment is larger than previous best segment. Then, reset upper
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# and lower bound to current cell
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elif self.map.data[y, x] == 0:
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if np.sqrt((ub_o[0]-lb_o[0])**2+(ub_o[1]-lb_o[1])**2) > \
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np.sqrt((ub_ls[0]-lb_ls[0])**2+(ub_ls[1]-lb_ls[1])**2):
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ub_ls = ub_o
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lb_ls = lb_o
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# Start new segment
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ub_o = (x, y)
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lb_o = (x, y)
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# If no segment was set (no obstacle between left and right border),
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# return original bounds of path
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if ub_ls == ub_p and lb_ls == ub_p:
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return wp.lb, wp.ub
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# Transform upper and lower bound cells to world coordinates
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ub_ls = self.map.m2w(ub_ls[0], ub_ls[1])
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lb_ls = self.map.m2w(lb_ls[0], lb_ls[1])
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# Check sign of upper and lower bound
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angle_ub = np.mod(np.arctan2(ub_ls[1] - wp.y, ub_ls[0] - wp.x)
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- wp.psi + math.pi, 2*math.pi) - math.pi
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angle_lb = np.mod(np.arctan2(lb_ls[1] - wp.y, lb_ls[0] - wp.x)
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- wp.psi + math.pi, 2*math.pi) - math.pi
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sign_ub = np.sign(angle_ub)
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sign_lb = np.sign(angle_lb)
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# Compute upper and lower bound of largest drivable area
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ub = sign_ub * np.sqrt((ub_ls[0]-wp.x)**2+(ub_ls[1]-wp.y)**2)
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lb = sign_lb * np.sqrt((lb_ls[0]-wp.x)**2+(lb_ls[1]-wp.y)**2)
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# Update member variables of waypoint
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wp.ub = ub
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wp.lb = lb
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wp.border_cells = (ub_ls, lb_ls)
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return lb, ub
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def show(self, display_drivable_area=True):
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"""
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Display path object on current figure.
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:param display_drivable_area: If True, display arrows indicating width
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of drivable area
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"""
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# Clear figure
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plt.clf()
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plt.imshow(np.flipud(self.map.data),cmap='gray',
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# Plot map in gray-scale and set extent to match world coordinates
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plt.imshow(np.flipud(self.map.data), cmap='gray',
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extent=[self.map.origin[0], self.map.origin[0] +
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self.map.width * self.map.resolution,
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self.map.origin[1], self.map.origin[1] +
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self.map.height * self.map.resolution])
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# plot reference path
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# Get x and y coordinates for all waypoints
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wp_x = np.array([wp.x for wp in self.waypoints])
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wp_y = np.array([wp.y for wp in self.waypoints])
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plt.scatter(wp_x, wp_y, color='k', s=5)
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if self.get_width_info:
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print('Min Width Left: {:f} m'.format(self.min_width[0]))
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print('Min Width Right: {:f} m'.format(self.min_width[1]))
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plt.quiver(wp_x, wp_y, self.width_info[1, :] - wp_x,
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self.width_info[2, :] - wp_y, scale=1, units='xy',
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width=0.05, color='#D4AC0D')
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plt.quiver(wp_x, wp_y, self.width_info[4, :] - wp_x,
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self.width_info[5, :] - wp_y, scale=1, units='xy',
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width=0.05, color='#BA4A00')
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# Get x and y locations of border cells for upper and lower bound
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wp_ub_x = np.array([wp.border_cells[0][0] for wp in self.waypoints])
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wp_ub_y = np.array([wp.border_cells[0][1] for wp in self.waypoints])
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wp_lb_x = np.array([wp.border_cells[1][0] for wp in self.waypoints])
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wp_lb_y = np.array([wp.border_cells[1][1] for wp in self.waypoints])
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# Plot waypoints
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plt.scatter(wp_x, wp_y, color='#99A3A4', s=3)
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# Plot arrows indicating drivable area
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if display_drivable_area:
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plt.quiver(wp_x, wp_y, wp_ub_x - wp_x, wp_ub_y - wp_y, scale=1,
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units='xy', width=0.2*self.resolution, color='#2ECC71',
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headwidth=1, headlength=2)
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plt.quiver(wp_x, wp_y, wp_lb_x - wp_x, wp_lb_y - wp_y, scale=1,
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units='xy', width=0.2*self.resolution, color='#2ECC71',
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headwidth=1, headlength=2)
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if __name__ == '__main__':
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# Create Map
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map = Map(file_path='map_race.png', origin=[-1, -2], resolution=0.005)
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# Select Path | 'Race' or 'Q'
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path = 'Race'
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# Create Map
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if path == 'Race':
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map = Map(file_path='map_race.png', origin=[-1, -2], resolution=0.005)
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# Specify waypoints
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# Floor 2
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# wp_x = [-9.169, -2.7, 11.9, 7.3, -6.95]
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# wp_y = [-15.678, -7.12, 10.9, 14.5, -3.31]
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# Race Track
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wp_x = [-0.75, -0.25, -0.25, 0.25, 0.25, 1.25, 1.25, 0.75, 0.75, 1.25, 1.25, -0.75, -0.75, -0.25]
|
||||
wp_y = [-1.5, -1.5, -0.5, -0.5, -1.5, -1.5, -1, -1, -0.5, -0.5, 0, 0, -1.5, -1.5]
|
||||
wp_x = [-0.75, -0.25, -0.25, 0.25, 0.25, 1.25, 1.25, 0.75, 0.75, 1.25,
|
||||
1.25, -0.75, -0.75, -0.25]
|
||||
wp_y = [-1.5, -1.5, -0.5, -0.5, -1.5, -1.5, -1, -1, -0.5, -0.5, 0, 0,
|
||||
-1.5, -1.5]
|
||||
# Specify path resolution
|
||||
path_resolution = 0.05 # m / wp
|
||||
|
||||
# Smooth Path
|
||||
reference_path = ReferencePath(map, wp_x, wp_y, path_resolution,
|
||||
smoothing_distance=5)
|
||||
smoothing_distance=5, max_width=0.22)
|
||||
elif path == 'Q':
|
||||
map = Map(file_path='map_floor2.png')
|
||||
wp_x = [-9.169, 11.9, 7.3, -6.95]
|
||||
wp_y = [-15.678, 10.9, 14.5, -3.31]
|
||||
# Specify path resolution
|
||||
path_resolution = 0.20 # m / wp
|
||||
reference_path = ReferencePath(map, wp_x, wp_y, path_resolution,
|
||||
smoothing_distance=5, max_width=1.5)
|
||||
else:
|
||||
reference_path = None
|
||||
print('Invalid path!')
|
||||
exit(1)
|
||||
|
||||
reference_path.show()
|
||||
plt.show()
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue