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main.py
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import numpy as np
import pybullet as p
import pybullet_data
import os
import gym
from gym import spaces
from gym.utils import seeding
import random
import time
import math
from config import opt
class ReachEnv(gym.Env):
def __init__(self, is_render=False, is_good_view=False):
"""
用于初始化reach环境中的各项参数，
Args:
is_render (bool): 是否创建场景可视化
is_good_view (bool): 是否创建更优视角
Returns:
None
"""
self.is_render = is_render
self.is_good_view = is_good_view
self.max_steps_one_episode = opt.max_steps_one_episode
if self.is_render:
p.connect(p.GUI)
else:
p.connect(p.DIRECT)
# 机械臂移动范围限制
self.x_low_obs = 0.2
self.x_high_obs = 0.7
self.y_low_obs = -0.3
self.y_high_obs = 0.3
self.z_low_obs = 0
self.z_high_obs = 0.55
# 机械臂动作范围限制
self.x_low_action = -0.4
self.x_high_action = 0.4
self.y_low_action = -0.4
self.y_high_action = 0.4
self.z_low_action = -0.6
self.z_high_action = 0.3
# 设置相机
p.resetDebugVisualizerCamera(cameraDistance=1.5,
cameraYaw=0,
cameraPitch=-40,
cameraTargetPosition=[0.55, -0.35, 0.2])
# 动作空间
self.action_space = spaces.Box(
low=np.array([self.x_low_action, self.y_low_action, self.z_low_action]),
high=np.array([self.x_high_action, self.y_high_action, self.z_high_action]),
dtype=np.float32)
# 状态空间
self.observation_space = spaces.Box(
low=np.array([self.x_low_obs, self.y_low_obs, self.z_low_obs, self.x_low_obs, self.y_low_obs, self.z_low_obs]),
high=np.array([self.x_high_obs, self.y_high_obs, self.z_high_obs, self.x_high_obs, self.y_high_obs, self.z_high_obs]),
dtype=np.float32)
# 时间步计数器
self.step_counter = 0
self.urdf_root_path = pybullet_data.getDataPath()
# joint damping coefficents
self.joint_damping = [
0.00001, 0.00001, 0.00001, 0.00001, 0.00001, 0.00001
]
# 初始关节角度
self.init_joint_positions = [
0.006418, 0.413184, -0.011401, -1.589317, 0.005379, 1.137684
]
self.orientation = p.getQuaternionFromEuler(
[0., -math.pi, math.pi / 2.])
self.seed()
self.reset()
def seed(self, seed=None):
"""随机种子"""
self.np_random, seed = seeding.np_random(seed)
return [seed]
def reset(self):
"""环境reset，获得初始state"""
# 初始化时间步计数器
self.step_counter = 0
p.resetSimulation()
# p.configureDebugVisualizer(p.COV_ENABLE_RENDERING, 0)
# 初始化重力以及运行结束标志
self.terminated = False
p.setGravity(0, 0, -9.8)
# 状态空间的限制空间可视化，以白线标识
p.addUserDebugLine(
lineFromXYZ=[self.x_low_obs, self.y_low_obs, 0],
lineToXYZ=[self.x_low_obs, self.y_low_obs, self.z_high_obs])
p.addUserDebugLine(
lineFromXYZ=[self.x_low_obs, self.y_high_obs, 0],
lineToXYZ=[self.x_low_obs, self.y_high_obs, self.z_high_obs])
p.addUserDebugLine(
lineFromXYZ=[self.x_high_obs, self.y_low_obs, 0],
lineToXYZ=[self.x_high_obs, self.y_low_obs, self.z_high_obs])
p.addUserDebugLine(
lineFromXYZ=[self.x_high_obs, self.y_high_obs, 0],
lineToXYZ=[self.x_high_obs, self.y_high_obs, self.z_high_obs])
p.addUserDebugLine(
lineFromXYZ=[self.x_low_obs, self.y_low_obs, self.z_high_obs],
lineToXYZ=[self.x_high_obs, self.y_low_obs, self.z_high_obs])
p.addUserDebugLine(
lineFromXYZ=[self.x_low_obs, self.y_high_obs, self.z_high_obs],
lineToXYZ=[self.x_high_obs, self.y_high_obs, self.z_high_obs])
p.addUserDebugLine(
lineFromXYZ=[self.x_low_obs, self.y_low_obs, self.z_high_obs],
lineToXYZ=[self.x_low_obs, self.y_high_obs, self.z_high_obs])
p.addUserDebugLine(
lineFromXYZ=[self.x_high_obs, self.y_low_obs, self.z_high_obs],
lineToXYZ=[self.x_high_obs, self.y_high_obs, self.z_high_obs])
# 载入平面
p.loadURDF(os.path.join(self.urdf_root_path, "plane.urdf"), basePosition=[0, 0, 0])
# 载入机械臂
search_path = "/home/blamlight/Github/mybullet/mycobot_description/urdf/mycobot_280_m5"
p.setAdditionalSearchPath(search_path)
urdf_file = "mycobot_280_m5.urdf"
self.kuka_id = p.loadURDF(urdf_file, useFixedBase=True)
# 载入桌子
# p.loadURDF(os.path.join(self.urdf_root_path, "table/table.urdf"), basePosition=[0.5, 0, -0.65])
# p.loadURDF(os.path.join(self.urdf_root_path, "tray/traybox.urdf"), basePosition=[0.55,0,0])
# object_id=p.loadURDF(os.path.join(self.urdf_root_path, "random_urdfs/000/000.urdf"), basePosition=[0.53,0,0.02])
# xpos = random.uniform(self.x_low_obs, self.x_high_obs)
# ypos = random.uniform(self.y_low_obs, self.y_high_obs)
# zpos = random.uniform(self.z_low_obs, self.z_high_obs) # TODO 原z=0.01
# ang = 3.14 * 0.5 + 3.1415925438 * random.random()
# orn = p.getQuaternionFromEuler([0, 0, ang])
# # 载入物体
# self.object_id = p.loadURDF("../models/cube_small_target_push.urdf",
# basePosition=[xpos, ypos, zpos],
# baseOrientation=[orn[0], orn[1], orn[2], orn[3]],
# useFixedBase=1)
# 关节角初始化
self.num_joints = p.getNumJoints(self.kuka_id)
for i in range(1, self.num_joints-1):
p.resetJointState(
bodyUniqueId=self.kuka_id,
jointIndex=i,
targetValue=self.init_joint_positions[i-1],
)
# for i in range(self.num_joints):
# print(p.getJointInfo(self.kuka_id, i))
self.robot_pos_obs = p.getLinkState(self.kuka_id,
self.num_joints - 1)[4]
# print(self.robot_pos_obs)
# logging.debug("init_pos={}\n".format(p.getLinkState(self.kuka_id,self.num_joints-1)))
p.stepSimulation()
# self.object_pos = p.getBasePositionAndOrientation(self.object_id)[0]
goal = [random.uniform(self.x_low_obs, self.x_high_obs),
random.uniform(self.y_low_obs, self.y_high_obs),
random.uniform(self.z_low_obs, self.z_high_obs)]
# self.object_state = np.array(
# p.getBasePositionAndOrientation(self.object_id)[0]).astype(
# np.float32)
# return np.array(self.object_pos).astype(np.float32), self.object_state
return np.hstack((np.array(self.robot_pos_obs).astype(np.float32)))
def step(self, action):
"""根据action获取下一步环境的state、reward、done"""
limit_x = [0.2, 0.7]
limit_y = [-0.3, 0.3]
limit_z = [0, 0.55]
def clip_val(val, limit):
if val < limit[0]:
return limit[0]
if val > limit[1]:
return limit[1]
return val
dv = opt.reach_ctr
dx = action[0] * dv
dy = action[1] * dv
dz = action[2] * dv
# 获取当前机械臂末端坐标
self.current_pos = p.getLinkState(self.kuka_id, self.num_joints - 1)[4]
# 计算下一步的机械臂末端坐标
self.new_robot_pos = [
clip_val(self.current_pos[0] + dx, limit_x), clip_val(self.current_pos[1] + dy, limit_y),
clip_val(self.current_pos[2] + dz, limit_z)
]
# 通过逆运动学计算机械臂移动到新位置的关节角度
self.robot_joint_positions = p.calculateInverseKinematics(
bodyUniqueId=self.kuka_id,
endEffectorLinkIndex=self.num_joints - 1,
targetPosition=[self.new_robot_pos[0], self.new_robot_pos[1], self.new_robot_pos[2]],
targetOrientation=self.orientation,
jointDamping=self.joint_damping,
)
# 使机械臂移动到新位置
for i in range(1, self.num_joints):
p.resetJointState(
bodyUniqueId=self.kuka_id,
jointIndex=i,
targetValue=self.robot_joint_positions[i-1],
)
p.stepSimulation()
# 在代码开始部分，如果定义了is_good_view，那么机械臂的动作会变慢，方便观察
if self.is_good_view:
time.sleep(0.05)
self.step_counter += 1
print(self.current_pos, self.new_robot_pos)
return 1
def close(self):
p.disconnect()
if __name__ == '__main__':
# 这一部分是做baseline，即让机械臂随机选择动作，看看能够得到的分数
env = ReachEnv(is_good_view=True, is_render=True)
print('env={}'.format(env))
obs = env.reset()
action = env.action_space.sample()
done = env.step(action)
sum_reward = 0
success_times = 0
for i in range(100):
env.reset()
for i in range(1000):
action = env.action_space.sample()
done = env.step(action)
# print('done={}'.format(done))
# time.sleep(0.1)
print()
print('sum_reward={}'.format(sum_reward))
print('success rate={}'.format(success_times / 50))