Python pybullet.getJointStates方法代码示例

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def _get_obs(self, forces, forces_human):
        torso_pos = np.array(p.getLinkState(self.robot, 15 if self.robot_type == 'pr2' else 0, computeForwardKinematics=True, physicsClientId=self.id)[0])
        tool_pos, tool_orient = p.getBasePositionAndOrientation(self.cup, physicsClientId=self.id)
        robot_joint_states = p.getJointStates(self.robot, jointIndices=self.robot_right_arm_joint_indices, physicsClientId=self.id)
        robot_joint_positions = np.array([x[0] for x in robot_joint_states])
        robot_pos, robot_orient = p.getBasePositionAndOrientation(self.robot, physicsClientId=self.id)
        if self.human_control:
            human_pos = np.array(p.getBasePositionAndOrientation(self.human, physicsClientId=self.id)[0])
            human_joint_states = p.getJointStates(self.human, jointIndices=self.human_controllable_joint_indices, physicsClientId=self.id)
            human_joint_positions = np.array([x[0] for x in human_joint_states])

        head_pos, head_orient = p.getLinkState(self.human, 23, computeForwardKinematics=True, physicsClientId=self.id)[:2]

        robot_obs = np.concatenate([tool_pos-torso_pos, tool_orient, tool_pos - self.target_pos, robot_joint_positions, head_pos-torso_pos, head_orient, forces]).ravel()
        if self.human_control:
            human_obs = np.concatenate([tool_pos-human_pos, tool_orient, tool_pos - self.target_pos, human_joint_positions, head_pos-human_pos, head_orient, forces_human]).ravel()
        else:
            human_obs = []

        return np.concatenate([robot_obs, human_obs]).ravel() 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def _get_obs(self, forces, forces_human):
        torso_pos = np.array(p.getLinkState(self.robot, 15 if self.robot_type == 'pr2' else 0, computeForwardKinematics=True, physicsClientId=self.id)[0])
        spoon_pos, spoon_orient = p.getBasePositionAndOrientation(self.spoon, physicsClientId=self.id)
        robot_right_joint_states = p.getJointStates(self.robot, jointIndices=self.robot_right_arm_joint_indices, physicsClientId=self.id)
        robot_right_joint_positions = np.array([x[0] for x in robot_right_joint_states])
        robot_pos, robot_orient = p.getBasePositionAndOrientation(self.robot, physicsClientId=self.id)
        if self.human_control:
            human_pos = np.array(p.getBasePositionAndOrientation(self.human, physicsClientId=self.id)[0])
            human_joint_states = p.getJointStates(self.human, jointIndices=self.human_controllable_joint_indices, physicsClientId=self.id)
            human_joint_positions = np.array([x[0] for x in human_joint_states])

        head_pos, head_orient = p.getLinkState(self.human, 23, computeForwardKinematics=True, physicsClientId=self.id)[:2]

        robot_obs = np.concatenate([spoon_pos-torso_pos, spoon_orient, spoon_pos-self.target_pos, robot_right_joint_positions, head_pos-torso_pos, head_orient, forces]).ravel()
        if self.human_control:
            human_obs = np.concatenate([spoon_pos-human_pos, spoon_orient, spoon_pos-self.target_pos, human_joint_positions, head_pos-human_pos, head_orient, forces_human]).ravel()
        else:
            human_obs = []

        return np.concatenate([robot_obs, human_obs]).ravel() 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def enforce_joint_limits(self, body):
        # Enforce joint limits
        joint_states = p.getJointStates(body, jointIndices=list(range(p.getNumJoints(body, physicsClientId=self.id))), physicsClientId=self.id)
        joint_positions = np.array([x[0] for x in joint_states])
        lower_limits = []
        upper_limits = []
        for j in range(p.getNumJoints(body, physicsClientId=self.id)):
            joint_info = p.getJointInfo(body, j, physicsClientId=self.id)
            joint_name = joint_info[1]
            joint_pos = joint_positions[j]
            lower_limit = joint_info[8]
            upper_limit = joint_info[9]
            if lower_limit == 0 and upper_limit == -1:
                lower_limit = -1e10
                upper_limit = 1e10
            lower_limits.append(lower_limit)
            upper_limits.append(upper_limit)
            # print(joint_name, joint_pos, lower_limit, upper_limit)
            if joint_pos < lower_limit:
                p.resetJointState(body, jointIndex=j, targetValue=lower_limit, targetVelocity=0, physicsClientId=self.id)
            elif joint_pos > upper_limit:
                p.resetJointState(body, jointIndex=j, targetValue=upper_limit, targetVelocity=0, physicsClientId=self.id)
        lower_limits = np.array(lower_limits)
        upper_limits = np.array(upper_limits)
        return lower_limits, upper_limits 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def enforce_hard_human_joint_limits(self):
        if not self.human_controllable_joint_indices:
            return
        # Enforce joint limits. Sometimes, external forces and break the person's hard joint limits.
        joint_states = p.getJointStates(self.human, jointIndices=self.human_controllable_joint_indices, physicsClientId=self.id)
        joint_positions = np.array([x[0] for x in joint_states])
        if self.human_joint_lower_limits is None:
            self.human_joint_lower_limits = []
            self.human_joint_upper_limits = []
            for i, j in enumerate(self.human_controllable_joint_indices):
                joint_info = p.getJointInfo(self.human, j, physicsClientId=self.id)
                joint_name = joint_info[1]
                joint_pos = joint_positions[i]
                lower_limit = joint_info[8]
                upper_limit = joint_info[9]
                self.human_joint_lower_limits.append(lower_limit)
                self.human_joint_upper_limits.append(upper_limit)
                # print(joint_name, joint_pos, lower_limit, upper_limit)
        for i, j in enumerate(self.human_controllable_joint_indices):
            if joint_positions[i] < self.human_joint_lower_limits[i]:
                p.resetJointState(self.human, jointIndex=j, targetValue=self.human_joint_lower_limits[i], targetVelocity=0, physicsClientId=self.id)
            elif joint_positions[i] > self.human_joint_upper_limits[i]:
                p.resetJointState(self.human, jointIndex=j, targetValue=self.human_joint_upper_limits[i], targetVelocity=0, physicsClientId=self.id) 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def _get_obs(self, forces, forces_human):
        torso_pos = np.array(p.getLinkState(self.robot, 15 if self.robot_type == 'pr2' else 0, computeForwardKinematics=True, physicsClientId=self.id)[0])
        state = p.getLinkState(self.tool, 1, computeForwardKinematics=True, physicsClientId=self.id)
        tool_pos = np.array(state[0])
        tool_orient = np.array(state[1]) # Quaternions
        robot_joint_states = p.getJointStates(self.robot, jointIndices=self.robot_left_arm_joint_indices, physicsClientId=self.id)
        robot_joint_positions = np.array([x[0] for x in robot_joint_states])
        robot_pos, robot_orient = p.getBasePositionAndOrientation(self.robot, physicsClientId=self.id)
        if self.human_control:
            human_pos = np.array(p.getBasePositionAndOrientation(self.human, physicsClientId=self.id)[0])
            human_joint_states = p.getJointStates(self.human, jointIndices=self.human_controllable_joint_indices, physicsClientId=self.id)
            human_joint_positions = np.array([x[0] for x in human_joint_states])

        # Human shoulder, elbow, and wrist joint locations
        shoulder_pos, shoulder_orient = p.getLinkState(self.human, 5, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        elbow_pos, elbow_orient = p.getLinkState(self.human, 7, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        wrist_pos, wrist_orient = p.getLinkState(self.human, 9, computeForwardKinematics=True, physicsClientId=self.id)[:2]

        robot_obs = np.concatenate([tool_pos-torso_pos, tool_orient, robot_joint_positions, shoulder_pos-torso_pos, elbow_pos-torso_pos, wrist_pos-torso_pos, forces]).ravel()
        if self.human_control:
            human_obs = np.concatenate([tool_pos-human_pos, tool_orient, human_joint_positions, shoulder_pos-human_pos, elbow_pos-human_pos, wrist_pos-human_pos, forces_human]).ravel()
        else:
            human_obs = []

        return np.concatenate([robot_obs, human_obs]).ravel() 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def _get_obs(self, forces, forces_human):
        torso_pos = np.array(p.getLinkState(self.robot, 15 if self.robot_type == 'pr2' else 0, computeForwardKinematics=True, physicsClientId=self.id)[0])
        state = p.getLinkState(self.tool, 1, computeForwardKinematics=True, physicsClientId=self.id)
        tool_pos = np.array(state[0])
        tool_orient = np.array(state[1]) # Quaternions
        robot_joint_states = p.getJointStates(self.robot, jointIndices=self.robot_left_arm_joint_indices, physicsClientId=self.id)
        robot_joint_positions = np.array([x[0] for x in robot_joint_states])
        robot_pos, robot_orient = p.getBasePositionAndOrientation(self.robot, physicsClientId=self.id)
        if self.human_control:
            human_pos = np.array(p.getBasePositionAndOrientation(self.human, physicsClientId=self.id)[0])
            human_joint_states = p.getJointStates(self.human, jointIndices=self.human_controllable_joint_indices, physicsClientId=self.id)
            human_joint_positions = np.array([x[0] for x in human_joint_states])

        # Human shoulder, elbow, and wrist joint locations
        shoulder_pos, shoulder_orient = p.getLinkState(self.human, 5, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        elbow_pos, elbow_orient = p.getLinkState(self.human, 7, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        wrist_pos, wrist_orient = p.getLinkState(self.human, 9, computeForwardKinematics=True, physicsClientId=self.id)[:2]

        robot_obs = np.concatenate([tool_pos-torso_pos, tool_orient, tool_pos - self.target_pos, self.target_pos-torso_pos, robot_joint_positions, shoulder_pos-torso_pos, elbow_pos-torso_pos, wrist_pos-torso_pos, forces]).ravel()
        if self.human_control:
            human_obs = np.concatenate([tool_pos-human_pos, tool_orient, tool_pos - self.target_pos, self.target_pos-human_pos, human_joint_positions, shoulder_pos-human_pos, elbow_pos-human_pos, wrist_pos-human_pos, forces_human]).ravel()
        else:
            human_obs = []

        return np.concatenate([robot_obs, human_obs]).ravel() 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def getAnglesPosition(self, joint_names):
        """
        Gets the position of the robot's joints in radians. If one of the joint
        doesn't exist, the method will raise a KeyError.

        Parameters:
            joint_names - List of string containing the names of the joints

        Returns:
            joint_positions - List of floats containing the joint's positions
        """
        indexes = [self.joint_dict[name].getIndex() for name in joint_names]

        return [state[0] for state in pybullet.getJointStates(
            self.robot_model,
            indexes,
            physicsClientId=self.physics_client)] 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def getAnglesVelocity(self, joint_names):
        """
        Gets the velocity of the robot's joints in rad/s. If one of the joint
        doesn't exist, the method will raise a KeyError.

        Parameters:
            joint_names - List of string containing the names of the joints

        Returns:
            joint_velocities - List of floats containing the joint's velocities
        """
        indexes = [self.joint_dict[name].getIndex() for name in joint_names]

        return [state[1] for state in pybullet.getJointStates(
            self.robot_model,
            indexes,
            physicsClientId=self.physics_client)] 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def getJointStates(robot):
	joint_states = p.getJointStates(robot, range(p.getNumJoints(robot)))
	joint_positions = [state[0] for state in joint_states]
	joint_velocities = [state[1] for state in joint_states]
	joint_torques = [state[3] for state in joint_states]
	return joint_positions, joint_velocities, joint_torques 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def getMotorJointStates(robot):
	joint_states = p.getJointStates(robot, range(p.getNumJoints(robot)))
	joint_infos = [p.getJointInfo(robot, i) for i in range(p.getNumJoints(robot))]
	joint_states = [j for j, i in zip(joint_states, joint_infos) if i[3] > -1]
	joint_positions = [state[0] for state in joint_states]
	joint_velocities = [state[1] for state in joint_states]
	joint_torques = [state[3] for state in joint_states]
	return joint_positions, joint_velocities, joint_torques 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def getMotorJointStates(self, robot):
        import pybullet as p
        joint_states = p.getJointStates(robot, range(p.getNumJoints(robot)))
        joint_infos = [p.getJointInfo(robot, i) for i in range(p.getNumJoints(robot))]
        joint_states = [j for j, i in zip(joint_states, joint_infos) if i[3] > -1]
        joint_positions = [state[0] for state in joint_states]
        joint_velocities = [state[1] for state in joint_states]
        joint_torques = [state[3] for state in joint_states]
        return joint_positions, joint_velocities, joint_torques 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def setup_human_joints(self, human, joints_positions, controllable_joints, use_static_joints=True, human_reactive_force=None, human_reactive_gain=0.05):
        if self.human_impairment != 'tremor':
            self.human_tremors = np.zeros(len(controllable_joints))
        elif len(controllable_joints) == 4:
            self.human_tremors = self.np_random.uniform(np.deg2rad(-20), np.deg2rad(20), size=len(controllable_joints))
        else:
            self.human_tremors = self.np_random.uniform(np.deg2rad(-10), np.deg2rad(10), size=len(controllable_joints))
        # Set starting joint positions
        human_joint_states = p.getJointStates(human, jointIndices=list(range(p.getNumJoints(human, physicsClientId=self.id))), physicsClientId=self.id)
        human_joint_positions = np.array([x[0] for x in human_joint_states])
        for j in range(p.getNumJoints(human, physicsClientId=self.id)):
            set_position = None
            for j_index, j_angle in joints_positions:
                if j == j_index:
                    p.resetJointState(human, jointIndex=j, targetValue=j_angle, targetVelocity=0, physicsClientId=self.id)
                    set_position = j_angle
                    break
            if use_static_joints and j not in controllable_joints:
                # Make all non controllable joints on the person static by setting mass of each link (joint) to 0
                p.changeDynamics(human, j, mass=0, physicsClientId=self.id)
                # Set velocities to 0
                p.resetJointState(human, jointIndex=j, targetValue=human_joint_positions[j] if set_position is None else set_position, targetVelocity=0, physicsClientId=self.id)

        # By default, all joints have motors enabled by default that prevent free motion. Disable these motors in human
        for j in range(p.getNumJoints(human, physicsClientId=self.id)):
            p.setJointMotorControl2(human, jointIndex=j, controlMode=p.VELOCITY_CONTROL, force=0, physicsClientId=self.id)

        self.enforce_joint_limits(human)

        if human_reactive_force is not None:
            # NOTE: This runs a Position / Velocity PD controller for each joint motor on the human
            human_joint_states = p.getJointStates(human, jointIndices=controllable_joints, physicsClientId=self.id)
            target_human_joint_positions = np.array([x[0] for x in human_joint_states])
            forces = [human_reactive_force * self.human_strength] * len(target_human_joint_positions)
            p.setJointMotorControlArray(human, jointIndices=controllable_joints, controlMode=p.POSITION_CONTROL, targetPositions=target_human_joint_positions, positionGains=np.array([human_reactive_gain]*len(forces)), forces=forces, physicsClientId=self.id) 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def get_motor_joint_states(self, robot):
        num_joints = p.getNumJoints(robot, physicsClientId=self.id)
        joint_states = p.getJointStates(robot, range(num_joints), physicsClientId=self.id)
        joint_infos = [p.getJointInfo(robot, i, physicsClientId=self.id) for i in range(num_joints)]
        joint_states = [j for j, i in zip(joint_states, joint_infos) if i[2] != p.JOINT_FIXED]
        joint_positions = [state[0] for state in joint_states]
        joint_velocities = [state[1] for state in joint_states]
        joint_torques = [state[3] for state in joint_states]
        return joint_positions, joint_velocities, joint_torques 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def _get_obs(self, forces, forces_human):
        torso_pos = np.array(p.getLinkState(self.robot, 15 if self.robot_type == 'pr2' else 0, computeForwardKinematics=True, physicsClientId=self.id)[0])
        tool_left_pos, tool_left_orient = p.getLinkState(self.robot, 78 if self.robot_type=='pr2' else 24 if self.robot_type=='sawyer' else 54 if self.robot_type=='baxter' else 9 if self.robot_type=='jaco' else 7, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        tool_right_pos, tool_right_orient = p.getLinkState(self.robot, 55 if self.robot_type=='pr2' else 24 if self.robot_type=='sawyer' else 31 if self.robot_type=='baxter' else 9 if self.robot_type=='jaco' else 7, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        robot_joint_states = p.getJointStates(self.robot, jointIndices=self.robot_both_arm_joint_indices, physicsClientId=self.id)
        robot_joint_positions = np.array([x[0] for x in robot_joint_states])
        robot_pos, robot_orient = p.getBasePositionAndOrientation(self.robot, physicsClientId=self.id)
        if self.human_control:
            human_pos = np.array(p.getBasePositionAndOrientation(self.human, physicsClientId=self.id)[0])
            human_joint_states = p.getJointStates(self.human, jointIndices=self.human_controllable_joint_indices, physicsClientId=self.id)
            human_joint_positions = np.array([x[0] for x in human_joint_states])

        # Human shoulder, elbow, and wrist joint locations
        shoulder_pos, shoulder_orient = p.getLinkState(self.human, 5, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        elbow_pos, elbow_orient = p.getLinkState(self.human, 7, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        wrist_pos, wrist_orient = p.getLinkState(self.human, 9, computeForwardKinematics=True, physicsClientId=self.id)[:2]
        waist_pos = np.array(p.getLinkState(self.human, 24, computeForwardKinematics=True, physicsClientId=self.id)[0])
        hips_pos = np.array(p.getLinkState(self.human, 27, computeForwardKinematics=True, physicsClientId=self.id)[0])
        shoulder_pos, elbow_pos, wrist_pos, waist_pos, hips_pos = np.array(shoulder_pos), np.array(elbow_pos), np.array(wrist_pos), np.array(waist_pos), np.array(hips_pos)

        robot_obs = np.concatenate([tool_left_pos-torso_pos, tool_left_orient, tool_right_pos-torso_pos, tool_right_orient, robot_joint_positions, shoulder_pos-torso_pos, elbow_pos-torso_pos, wrist_pos-torso_pos, waist_pos-torso_pos, hips_pos-torso_pos, forces]).ravel()
        if self.human_control:
            human_obs = np.concatenate([tool_left_pos-human_pos, tool_left_orient, tool_right_pos-human_pos, tool_right_orient, human_joint_positions, shoulder_pos-human_pos, elbow_pos-human_pos, wrist_pos-human_pos, waist_pos-human_pos, hips_pos-human_pos, forces_human]).ravel()
        else:
            human_obs = []

        return np.concatenate([robot_obs, human_obs]).ravel() 

# 需要导入模块: import pybullet [as 别名]
# 或者: from pybullet import getJointStates [as 别名]
def _getGripper(self):
        vs = [v[0] for v in pb.getJointStates(self.handle,
            self.stable_gripper_indices)]
        return np.array([np.round(-np.mean(vs),1)])