机械臂柔顺控制(包含阻抗控制、导纳控制、混合力位控制)基于ros的c++代码

上传者: 51027140 | 上传时间: 2024-08-08 11:56:26 | 文件大小: 11.9MB | 文件类型: ZIP
在机器人技术领域,柔顺控制是提升机械臂与环境交互性能的关键技术,它涉及到机械臂在执行任务时对外力的感知和响应。本项目聚焦于三种柔顺控制策略:阻抗控制、导纳控制和混合力位控制,并且所有代码都是基于ROS(Robot Operating System)的C++实现。ROS是一个广泛使用的开源机器人软件框架,提供了丰富的工具和库来帮助开发者构建复杂的机器人系统。 1. 阻抗控制:阻抗控制是一种模拟物理材料阻抗特性的控制策略,使机械臂能够像弹簧一样对外力产生反应。在阻抗控制中,机械臂的行为可以被定义为一个机械系统,其中,阻抗参数决定了机械臂对扰动的响应。例如,高阻抗意味着机械臂更刚硬,对外力反应较小;低阻抗则使机械臂更柔软,更容易随外力移动。通过调整这些参数,可以实现机械臂的精细操作,如装配任务。 2. 导纳控制:导纳控制与阻抗控制相反,它是从环境到机械臂的力传递特性进行建模。在导纳控制中,机械臂被设计为一个导体,允许外部力通过并转化为运动。这种控制方法主要用于实现人机协作,确保人类操作者可以轻松地引导机械臂完成任务,同时保护人的安全。导纳控制器通常会包含力传感器和位置传感器,用于实时监测和处理输入。 3. 混合力位控制:混合力位控制结合了阻抗控制和导纳控制的优点,允许机械臂在力模式和位置模式之间灵活切换。在某些情况下,机械臂可能需要精确的位置控制,而在其他情况下,可能需要对环境的力反馈作出反应。混合力位控制可以根据任务需求动态调整控制策略,提供更灵活的交互体验。 这个基于ROS的C++实现可能包括以下组件: - **硬件接口**:与实际机械臂的通讯模块,如驱动器和传感器的读取。 - **控制器**:实现阻抗、导纳和混合力位控制算法的代码。 - **状态估计**:利用传感器数据估计机械臂的位置、速度和力。 - **力传感器处理**:读取并处理来自力传感器的数据。 - **话题发布与订阅**:通过ROS消息系统,控制器与硬件接口和其他ROS节点进行通信。 - **参数服务器**:存储和管理控制参数,如阻抗和导纳的设定值。 - **示教器**:可能包括一个用户界面,允许操作员对机械臂的运动进行编程或实时控制。 使用ROS的C++实现使得代码可移植性增强,且能与其他ROS兼容的库和工具无缝集成,如Gazebo仿真环境、MoveIt!运动规划库等。学习和理解这个项目将有助于深入掌握机器人柔顺控制理论及其在实际应用中的实现细节。

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( 380 个子文件 11.9MB ) 机械臂柔顺控制(包含阻抗控制、导纳控制、混合力位控制)基于ros的c++代码
MirMoveBase.action 2.33KB
SetMode.action 946B
model.config 271B
hardware_interface.cpp 52.63KB
dashboard_client_ros.cpp 14.12KB
robot_state_helper.cpp 10.64KB
Impedance.cpp 10.44KB
hybrid_position_force_control.cpp 8.99KB
Admittance.cpp 8.68KB
calibration_test.cpp 8.18KB
calibration.cpp 8.13KB
control_strategy.cpp 7.86KB
HybridAdmittance.cpp 7.55KB
cartesian_position_controller.cpp 6.40KB
hardware_interface_node.cpp 5.12KB
joint_torque_controller.cpp 5.02KB
cartesian_velocity_controller.cpp 4.99KB
controller_stopper.cpp 4.98KB
calibration_correction.cpp 4.96KB
urcl_log_handler.cpp 3.89KB
hybrid_position_force_control_node.cpp 3.28KB
HybridAdmittance_node.cpp 2.74KB
filter.cpp 2.66KB
Admittance_node.cpp 2.52KB
calibration_consumer.cpp 2.21KB
Impedance_node.cpp 1.92KB
dashboard_client_node.cpp 1.58KB
logger.cpp 1.40KB
controller_stopper_node.cpp 1.37KB
robot_state_helper_node.cpp 1.34KB
control_strategy_node.cpp 1.34KB
WrenchSignalGenerate.cpp 1.07KB
upperarm.dae 2.94MB
upperarm.dae 1.92MB
shoulder.dae 1.71MB
wrist2.dae 1.48MB
forearm.dae 1.40MB
wrist1.dae 1.27MB
forearm.dae 1.09MB
shoulder.dae 987.82KB
wrist1.dae 930.13KB
wrist2.dae 928.97KB
base.dae 349.66KB
base.dae 152.94KB
wrist3.dae 124.70KB
wrist3.dae 64.53KB
Hybrid_Position_Force_Control.gif 1.50MB
Hybrid_Admittance.gif 532.45KB
Admittance.gif 513.69KB
.gitignore 8B
hardware_interface.h 12.23KB
kinematics_base.h 6.49KB
kinematics_base.h 6.49KB
kinematics_base.h 6.31KB
calibration.h 6.26KB
KDL_Base.h 5.29KB
dashboard_client_ros.h 4.88KB
Impedance.h 4.06KB
control_strategy.h 3.90KB
robot_state_helper.h 3.80KB
hybrid_position_force_control.h 3.75KB
urcl_log_handler.h 3.62KB
cartesian_position_controller.h 3.54KB
joint_torque_controller.h 3.21KB
HybridAdmittance.h 3.19KB
Admittance.h 3.17KB
cartesian_velocity_controller.h 3.09KB
controller_stopper.h 2.12KB
calibration_consumer.h 1.89KB
filter.h 841B
logger.h 674B
control_strategy_params.h 272B
ur_logo.jpg 58.44KB
e-Series.jpg 41.30KB
ur_control.launch 7.62KB
ur_common.launch 4.91KB
ur5e_bringup.launch 4.50KB
ur5e_bringup.launch 3.69KB
mir_gazebo_common.launch 3.38KB
mir.launch 3.27KB
mir_empty_world.launch 2.83KB
load_ur.launch 2.34KB
ur5_bringup.launch 2.31KB
HybridAdmittance.launch 1.07KB
load_ur5e.launch 1.03KB
load_ur5.launch 1.02KB
hybrid_position_force_control.launch 934B
mir_debug_urdf.launch 817B
Admittance.launch 714B
Impedance.launch 703B
fake_localization.launch 674B
load_controller.launch 661B
load_controller.launch 661B
mir_maze_world.launch 604B
calibration_correction.launch 519B
view_ur5e.launch 430B
view_ur5.launch 429B
control_strategy.launch 422B
upload_mir_urdf.launch 411B
example_rviz.launch 165B
......
文件过多,未全部展示
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