ticks_to_mm = 0.349
robot_width = 150.0
# The start pose we obtained miraculously.
pose = (1850.0, 1897.0, 3.717551306747922)
# Read the logfile which contains all scans.
logfile = LegoLogfile()
logfile.read("robot4_motors.txt")
logfile.read("robot4_scan.txt")
# Iterate over all positions.
out_file = file("estimate_wall_transform.txt", "w")
for i in xrange(len(logfile.scan_data)):
# Compute the new pose.
pose = filter_step(pose, logfile.motor_ticks[i], ticks_to_mm,
robot_width, scanner_displacement)
# Subsample points.
subsampled_points = get_subsampled_points(logfile.scan_data[i])
world_points = [
LegoLogfile.scanner_to_world(pose, c) for c in subsampled_points
]
# Get the transformation
left, right = get_corresponding_points_on_wall(world_points)
trafo = estimate_transform(left, right, fix_scale=True)
# Correct the initial position using trafo. Also transform points.
if trafo:
pose = correct_pose(pose, trafo)
world_points = [apply_transform(trafo, p) for p in world_points]
# Read the logfile which contains all scans.
logfile = LegoLogfile()
logfile.read("robot4_motors.txt")
logfile.read("robot4_scan.txt")
# Also read the reference cylinders (the map).
logfile.read("robot_arena_landmarks.txt")
reference_cylinders = [l[1:3] for l in logfile.landmarks]
# Iterate over all positions.
out_file = file("find_cylinder_pairs.txt", "w")
for i in xrange(len(logfile.scan_data)):
# Compute the new pose.
pose = filter_step(pose, logfile.motor_ticks[i],
ticks_to_mm, robot_width,
scanner_displacement)
# Extract cylinders, also convert them to world coordinates.
cartesian_cylinders = compute_scanner_cylinders(
logfile.scan_data[i],
depth_jump, minimum_valid_distance, cylinder_offset)
world_cylinders = [LegoLogfile.scanner_to_world(pose, c)
for c in cartesian_cylinders]
# For every cylinder, find the closest reference cylinder.
cylinder_pairs = find_cylinder_pairs(
world_cylinders, reference_cylinders, max_cylinder_distance)
# Write to file.
# The pose.
