526 lines
16 KiB
Python
526 lines
16 KiB
Python
import logging
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import numpy as np
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from math import *
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from logs import *
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from dynamixel_sdk import *
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from xbox import *
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import time
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# DEBUG
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LEGS_LOG_LEVEL = logging.WARNING
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CONTROLLER_LOG_LEVEL = logging.CRITICAL
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# Variables configurations
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l1h = 0.049
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l1v = 0.032
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l1 = l1h # this is not the real distance as it's not the one needed to calculate position.
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# length between motor 2 and motor 3.
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l2h = 0.0605
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l2v = 0.02215
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l2 = sqrt(l2h ** 2 + l2v ** 2)
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# length between motor 3 and end of the leg.
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l3h = 0.012
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l3v = 0.093
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l3 = sqrt(l3h ** 2 + l3v ** 2)
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# offset of the 'head', the legs isolated at each end.
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tete_x = 0.095
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# offset of the legs at the side.
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patte_y = 0.032
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patte_x = 0.079
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num_patte = 6
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# Logs functions
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legsLogger = setup_logger("legs", LEGS_LOG_LEVEL)
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controllerLogger = setup_logger("Controller", CONTROLLER_LOG_LEVEL)
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# Initialize controller
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xbox = Xbox(controllerLogger)
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CONTROLLER_MODE = xbox.initialized
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xbox.mode_count = 5
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neutral_position = np.array([
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[0.1, 0.16, -0.15],
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[-0.1, 0.16, -0.15],
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[-0.2, -0.00, -0.15],
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[-0.1, -0.16, -0.15],
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[0.1, -0.16, -0.15],
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[0.2, 0, -0.15]
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])
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REAL = 0
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# Robot setup
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if REAL == 1:
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portHandler = PortHandler("/dev/ttyUSB0")
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packetHandler = PacketHandler(1.0)
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portHandler.openPort()
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x = portHandler.setBaudRate(1000000)
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print(x)
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ADDR_GOAL_POSITION = 30
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ids = []
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for id in range(0, 100):
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model_number, result, error = packetHandler.ping(portHandler, id)
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if model_number == 12:
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print(f"Found AX-12 with id: {id}")
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ids.append(id)
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time.sleep(0.01)
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# Done
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def interpol2(point2, point1, t):
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x1, y1, z1 = point1
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x2, y2, z2 = point2
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return t * x1 + (1 - t) * x2, t * y1 + (1 - t) * y2, t * z1 + (1 - t) * z2
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def get_current_step(t, step_duration, movement_duration):
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time_passed = 0
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for i in range(len(step_duration)):
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time_passed += step_duration[i]
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if t % movement_duration < time_passed:
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return i
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def get_current_step_advancement(t, movement_duration, step_duration, current_step):
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current_step = get_current_step(t, step_duration, movement_duration)
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t = t % movement_duration
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for i in range(0, current_step):
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t -= step_duration[i]
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return t / step_duration[current_step]
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def inverse(x, y, z):
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"""
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"""
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# Dimensions (m)
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z += l1v
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theta0 = atan2(y, x)
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l = sqrt((sqrt(x ** 2 + y ** 2) - l1) ** 2 + z ** 2)
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# l = sqrt((x - l1h*cos(theta0)) ** 2 + (y - l1h*sin(theta0)) ** 2 + (z + l1v) ** 2)
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param2 = -1 * (-(l ** 2) + l2 ** 2 + l3 ** 2) / (2 * l2 * l3)
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if param2 > 1 or param2 < -1:
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legsLogger.warning("fTentative d'acces a une position impossible (param2) ({x}, {y}, {z})")
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param2 = 1 if param2 > 1 else -1
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theta2 = acos(param2)
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param1 = (-l3 ** 2 + l2 ** 2 + l ** 2) / (2 * l2 * l)
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if param1 > 1 or param1 < -1:
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legsLogger.warning(f"Tentative d'acces a une position impossible (param1) ({x}, {y}, {z})")
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param1 = 1 if param1 > 1 else -1
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theta1 = acos(param1) + asin(z / l)
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# return [-theta0, theta1, theta2]
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angle1 = atan(l2v / l2h)
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return [-theta0, theta1 + angle1, theta2 + angle1 - pi / 2 + atan(l3h / l3v)]
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# return [0, angle1 , angle1 -pi/2 + atan(l3h/l3v)]
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def legs(targets_robot):
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"""
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takes a list of target and offsets it to be in the legs referential
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"""
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targets = [0] * 18
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cos_val = [0, 0, -1, 0, 0, 1]
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sin_val = [-1, -1, 0, 1, 1, 0]
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offset_x = [-patte_x, -patte_x, -tete_x, -patte_x, -patte_x, -tete_x]
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offset_y = [patte_y, -patte_y, 0, patte_y, -patte_y, 0]
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for i in range(6):
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target_x, target_y, target_z = targets_robot[i]
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target_x_tmp = cos_val[i] * target_x - sin_val[i] * target_y
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target_y = sin_val[i] * target_x + cos_val[i] * target_y
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target_x = target_x_tmp
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target_x += offset_x[i]
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target_y += offset_y[i]
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alpha, beta, gamma = inverse(target_x, target_y, target_z)
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targets[3 * i] = alpha
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targets[3 * i + 1] = beta
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targets[3 * i + 2] = gamma
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return targets
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def naive_walk(t, speed_x, speed_y):
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slider_max = 0.200
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real_position = np.copy(neutral_position)
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movement_x = np.array([
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[0.00, 0, 0],
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[0.04, 0, 0],
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[-0.04, 0, 0],
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])
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movement_y = np.array([
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[0.0, 0, 0],
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[0, 0.04, 0],
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[0, -0.04, 0],
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])
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movement_z = np.array([
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[0, 0, 0.08],
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[0, 0, -0.02],
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[0, 0, -0.02]
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])
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# duration of each step of the movement
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step_duration = np.array([0.05, 0.3, 0.05])
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step_count = len(movement_z)
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movement_duration = np.sum(step_duration)
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assert len(
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step_duration) == step_count, f"all movements steps must have a length, currently, {len(step_duration)}/{step_count} have them"
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def get_next_step(t):
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return floor((get_current_step(t, step_duration, movement_duration) + 1) % step_count)
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offsets = np.array([0, 1 / 3, 2 / 3, 0, 1 / 3, 2 / 3]) * movement_duration # offset between each leg
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assert len(offsets) == num_patte, f"all offsets must be set, currently, {len(offsets)}/{num_patte} have them"
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for patte in range(num_patte):
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time = t + offsets[patte]
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mov_index_start = get_current_step(time, step_duration, movement_duration)
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mov_index_end = get_next_step(time)
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mov_start_x = normalize(movement_x[mov_index_start], slider_max, speed_x)
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mov_end_x = normalize(movement_x[mov_index_end], slider_max, speed_x)
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mov_start_y = normalize(movement_y[mov_index_start], slider_max, speed_y)
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mov_end_y = normalize(movement_y[mov_index_end], slider_max, speed_y)
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mov_start_z = movement_z[mov_index_start]
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mov_end_z = movement_z[mov_index_end]
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mov_start = neutral_position[patte] + mov_start_z + mov_start_x + mov_start_y
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mov_end = neutral_position[patte] + mov_end_z + mov_end_x + mov_end_y
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(real_position[patte][0],
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real_position[patte][1],
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real_position[patte][2]) = interpol2(mov_start, mov_end,
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get_current_step_advancement(time, movement_duration, step_duration,
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mov_index_start))
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legsLogger.debug(
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f"[{patte}] [{mov_index_start}->{mov_index_end}], start: {mov_start}, end: {mov_end}, current ({real_position[patte][0]}, {real_position[patte][1]}, {real_position[patte][2]})")
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return legs(real_position)
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def normalize(matrix, slider_max, speed):
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return (matrix / slider_max) * speed
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counter = 0
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def convert_to_robot(positions):
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global counter
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counter += 1
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if counter % 2 != 0:
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return
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print(positions)
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index = [
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11, 12, 13,
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41, 42, 43,
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21, 22, 23,
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51, 52, 53,
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61, 62, 63,
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31, 32, 33]
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dir = [-1] * 18
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for i in range(len(positions)):
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value = int(512 + positions[i] * 150 * dir[i])
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packetHandler.write2ByteTxOnly(portHandler, index[i], ADDR_GOAL_POSITION, value)
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# packetHandler.writeTxOnly(portHandler, index[i], ADDR_GOAL_POSITION, 2,
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# bytes(value))
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def stand(x1, y1, x2, y2):
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return [
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0, 0, 0,
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0, 0, 0,
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x1, 0, 0,
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0, -0.5, 0,
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0, -0.5, 0,
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y1, 0, 0
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]
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def walk(t, sx, sy, sr):
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xboxdata = xbox.get_data()
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val = xboxdata["x1"]
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max_slider = 0.200
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controllerLogger.debug(xboxdata)
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if xbox.mode == 0:
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positions = static()
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elif xbox.mode == 1:
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positions = jump(xboxdata["y2"])
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elif xbox.mode == 2:
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positions = dino_naive(t, max_slider * xboxdata["y1"], max_slider * xboxdata["x1"], max_slider * xboxdata["y2"],
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max_slider * xboxdata["x2"], max_slider * (xboxdata["r2"] + 1))
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elif xbox.mode == 3:
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positions = naive_walk(t, max_slider * xboxdata["x1"], max_slider * xboxdata["y1"])
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elif xbox.mode == 4:
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positions = dev(t, max_slider * xboxdata["y1"], -1 * max_slider * xboxdata["x1"], xboxdata["x2"] * max_slider,
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max_slider * xboxdata["y2"])
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elif xbox.mode == 5:
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positions = stand(xboxdata["x1"], xboxdata["y1"], xboxdata["x2"], xboxdata["y2"])
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print(positions)
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if REAL == 1:
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convert_to_robot(positions)
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return positions
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def static():
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return legs(neutral_position)
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# Walk V2
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def dev(t, speed_x, speed_y, speed_r, y2):
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"""
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x1: speed along the x-axis
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y1: speed along the y-axis
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x2: rotational speed along the z-axis
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"""
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max_dist = 0.3
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print(speed_r)
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def get_rotation_center(speed_x, speed_y, theta_point):
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norm = sqrt(speed_x ** 2 + speed_y ** 2)
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r = 1000 if theta_point == 0 else norm / theta_point
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if norm != 0:
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return np.array([speed_y, -speed_x]) / norm * r
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else:
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return 0, 0
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center_x, center_y = get_rotation_center(speed_x, speed_y, speed_r)
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legsLogger.debug(f"rotation center: center_x: {center_x}, center_y: {center_y}")
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real_position = np.copy(neutral_position)
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movement_z = np.array([
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[0, 0, 0.02],
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[0, 0, -0.01],
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[0, 0, -0.01]
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])
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step_duration = np.array([0.15, 0.3, 0.15])
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step_count = len(movement_z)
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movement_duration = np.sum(step_duration)
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assert len(
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step_duration) == step_count, f"all movements steps must have a length, currently, {len(step_duration)}/{step_count} have them"
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def get_next_step(t):
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return floor((get_current_step(t, step_duration, movement_duration) + 1) % step_count)
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offsets = np.array([0, 1 / 3, 2 / 3, 0, 1 / 3, 2 / 3]) * movement_duration # offset between each leg
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assert len(offsets) == num_patte, f"all offsets must be set, currently, {len(offsets)}/{num_patte} have them"
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# used to cap the speed to a max
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max_radius = 0
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for patte in range(num_patte):
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x1, y1 = real_position[patte][0], real_position[patte][1]
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circle_radius = sqrt((center_x - x1) ** 2 + (center_y - y1) ** 2)
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max_radius = max(max_radius, circle_radius)
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for patte in range(num_patte):
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time = t + offsets[patte]
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mov_index_start = get_current_step(time, step_duration, movement_duration)
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mov_index_end = get_next_step(time)
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step_adv = get_current_step_advancement(time, movement_duration, step_duration, mov_index_start)
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mov_start_z = movement_z[mov_index_start]
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mov_end_z = movement_z[mov_index_end]
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mov_start = neutral_position[patte] + mov_start_z
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mov_end = neutral_position[patte] + mov_end_z
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(real_position[patte][0],
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real_position[patte][1],
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real_position[patte][2]) = interpol2(mov_start, mov_end, step_adv)
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x1, y1 = real_position[patte][0], real_position[patte][1]
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circle_radius = sqrt((center_x - x1) ** 2 + (center_y - y1) ** 2)
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cur_theta = acos((x1 - center_x) / circle_radius)
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if y1 < center_y:
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cur_theta *= -1
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if speed_r != 0:
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speed = sqrt(speed_x ** 2 + speed_y ** 2) * (speed_r / abs(speed_r))
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else:
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speed = sqrt(speed_x ** 2 + speed_y ** 2)
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if speed == 0:
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speed = speed_r
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dthteta = speed * (1 / max_radius * max_dist)
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legsLogger.info(f"speed: {speed}, dthteta: {dthteta}")
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if mov_index_start == 0:
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# midair part 1
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theta_offset = dthteta * (- step_adv)
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elif mov_index_start == 1:
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# moving part
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theta_offset = dthteta * (step_adv - 0.5) * 2
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else:
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# midair part 1
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theta_offset = dthteta * (1 - step_adv)
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wanted_theta = cur_theta + theta_offset
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wanted_x = center_x + circle_radius * cos(wanted_theta)
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wanted_y = center_y + circle_radius * sin(wanted_theta)
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real_position[patte][0] = wanted_x
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real_position[patte][1] = wanted_y
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if REAL:
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return legs(real_position)
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return legs(real_position), [center_x, center_y]
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def jump(sy):
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offset = np.array([
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[0, 0, -0.15],
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[0, 0, -0.15],
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[0, 0, -0.15],
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[0, 0, -0.15],
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[0, 0, -0.15],
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[0, 0, -0.15]
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])
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offset *= sy
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return legs(neutral_position + offset)
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# based on walk V1
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def dino_naive(t, speed_x, speed_y, hz, hy, hx):
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slider_max = 0.200
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real_position = np.copy(neutral_position)
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movement_x = np.array([
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[0.00, 0, 0],
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[0.04, 0, 0],
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[-0.04, 0, 0],
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])
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movement_y = np.array([
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[0.0, 0, 0],
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[0, 0.04, 0],
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[0, -0.04, 0],
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])
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movement_z = np.array([
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[0, 0, 0.08],
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[0, 0, -0.02],
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[0, 0, -0.02]
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])
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# duration of each step of the movement
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step_duration = np.array([0.05, 0.3, 0.05])
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step_count = len(movement_z)
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movement_duration = np.sum(step_duration)
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assert len(
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step_duration) == step_count, f"all movements steps must have a length, currently, {len(step_duration)}/{step_count} have them"
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def get_next_step(t):
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return floor((get_current_step(t, step_duration, movement_duration) + 1) % step_count)
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offsets = np.array([0, 1 / 3, 2 / 3, 0, 1 / 3, 2 / 3]) * movement_duration # offset between each leg
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assert len(offsets) == num_patte, f"all offsets must be set, currently, {len(offsets)}/{num_patte} have them"
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for patte in range(num_patte):
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if patte in [2, 5]:
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continue
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time = t + offsets[patte]
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mov_index_start = get_current_step(time, step_duration, movement_duration)
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mov_index_end = get_next_step(time)
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mov_start_x = normalize(movement_x[mov_index_start], slider_max, speed_x)
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mov_end_x = normalize(movement_x[mov_index_end], slider_max, speed_x)
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mov_start_y = normalize(movement_y[mov_index_start], slider_max, speed_y)
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mov_end_y = normalize(movement_y[mov_index_end], slider_max, speed_y)
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mov_start_z = movement_z[mov_index_start]
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mov_end_z = movement_z[mov_index_end]
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mov_start = neutral_position[patte] + mov_start_z + mov_start_x + mov_start_y
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mov_end = neutral_position[patte] + mov_end_z + mov_end_x + mov_end_y
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(real_position[patte][0],
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real_position[patte][1],
|
|
real_position[patte][2]) = interpol2(mov_start, mov_end,
|
|
get_current_step_advancement(time, movement_duration, step_duration,
|
|
mov_index_start))
|
|
|
|
real_position[2][2] = -0.1
|
|
real_position[2][0] = -0.28
|
|
|
|
real_position[5][2] = 0.05 + hz
|
|
real_position[5][0] = 0.25 + hx
|
|
real_position[5][1] = hy
|
|
|
|
return legs(real_position)
|
|
|
|
|
|
def robot_input():
|
|
print("Send motors wave (press enter)")
|
|
input()
|
|
for id in ids:
|
|
packetHandler.write2ByteTxRx(portHandler, id, ADDR_GOAL_POSITION, 512)
|
|
input()
|
|
angle = [512, 624, 400, 512, 624, 400]
|
|
for id in range(1, 7):
|
|
packetHandler.write2ByteTxRx(portHandler, id * 10 + 1, ADDR_GOAL_POSITION, angle[id - 1])
|
|
input()
|
|
|
|
# Dino mode
|
|
packetHandler.write2ByteTxRx(portHandler, 12, ADDR_GOAL_POSITION, 650)
|
|
packetHandler.write2ByteTxRx(portHandler, 42, ADDR_GOAL_POSITION, 650)
|
|
packetHandler.write2ByteTxRx(portHandler, 43, ADDR_GOAL_POSITION, 400)
|
|
|
|
input()
|
|
for id in ids:
|
|
packetHandler.write2ByteTxRx(portHandler, id, ADDR_GOAL_POSITION, 512)
|
|
# t = 0.0
|
|
# while True:
|
|
# print("Send motors wave (press enter)")
|
|
# angle = 512 + int(50 * np.sin(t))
|
|
# print(angle)
|
|
# packetHandler.write2ByteTxRx(portHandler, 53, ADDR_GOAL_POSITION, angle)
|
|
# time.sleep(0.001)
|
|
# t += 0.01
|
|
|
|
|
|
if __name__ == "__main__":
|
|
print("N'exécutez pas ce fichier, mais simulator.py")
|