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 = open("estimate_wall_transform.txt", "w") for i in range(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] else: world_points = []
# 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("icp_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. # You may play withe the number of iterations here to see # the effect on the trajectory! trafo = get_icp_transform(world_points, iterations = 40) # Correct the initial position using trafo. pose = correct_pose(pose, trafo) # Write to file. # The pose. print >> out_file, "F %f %f %f" % pose # Write the scanner points and corresponding points.