MoveIt Tutorial学习笔记 - 二
http://docs.ros.org/kinetic/api/moveit_tutorials/html/index.html 阅读学习笔记 ；保存成.md文件查看
#### Planning with Approximated Constraint Manifolds 使用近似约束流型进行规划
- reduces planning time.
将用户设定的约束，先转化为Approximated Constraint Manifolds，并保存到一个database；后续直接基于这个database进行运动规划，以减少运动规划的时间；
compute an approximation of the constraint manifold beforehand and perform trajectory planning in that. The OMPL plugin contains the functionality to do that for a given set of constraints and save it in a database. In later instances the database can be loaded to use for constrained planning with any OMPL planner which strongly reduces planning time.
- Database Construction 数据库的构建
adding the constraints to the ConstraintsLibrary object the database can be constructed by callingsaveApproximationConstraints()
The function requires four parameters:
1.constraints message (moveit_msgs::Constraints)
2.robot description (std::string)
3.planning scene (planning_scene::PlanningScenePtr)
4.construction options (ompl_interface::ConstraintApproximationConstructionOptions)
- Database Loading and Usage
- - Loading：
The constraints database must be loaded at launch of the move group node by setting the ros parameter://必须在启动move group节点时进行加载
- - Usage：
For planning just initialize the constraints message as always and set the messages name to the exact name that was used to construct the database. Also you need to specify the same values and tolerances again since by default the planner just samples over the states but does not necessary follow the constraints during interpolation for path planning. A correctly named constraint message without initialized constraints would use the database but can therefore lead to invalid trajectories anyway.
//初始化constraints message，该message的name要与用于生成database的message name保持一致；不需要对constraints message中的constraints进行初始化；规划时将自动调用先前生成的database；
#### Pick and Place
In MoveIt!, grasping is done using the MoveGroup interface.
相关数据类型：主要对这两个数据类型中各功能元素的理解；设定了pick和place相关的动作、姿态等
moveit_msgs::Grasp //grasp
moveit_msgs::PlaceLocation //place
pick and place动作接口：
move_group.setSupportSurfaceName("table1");
move_group.pick("object", grasps);
group.setSupportSurfaceName("table2");
group.place("object", place_location);
### Integration with a New Robot
#### MoveIt! Setup Assistant
Step 3: Add Virtual Joints
Virtual joints are used primarily to attach the robot to the world.
Step 7: Add Passive Joints
This tells the planners that they cannot (kinematically) plan for these joints because they can’t be directly controlled.
Step 8: 3D Perception
configuring the 3D sensors sensors_3d.yaml.
Step 9: Gazebo Simulation
help you simulate your robot with Gazebo by generating a new Gazebo compatible urdf if needed.
Step 10: ROS Control
auto generate simulated controllers to actuate the joints of your robot.
基于ros_control框架
#### URDF and SRDF
Safety Limits
If the “soft_lower_limit” and the “soft_upper_limit” in the safety_controller are set to 0.0, your joint will be unable to move.
#### Low Level Controllers
configuring MoveIt! with the controllers on your robot. We will assume that your robot offers a FollowJointTrajectory action service for the arms on your robot and (optionally) a GripperCommand service for your gripper. If your robot does not offer this we recommend the ROS control framework for easily adding this functionality around your hardware communication layer.
//基于ros_control framework, 增加FollowJointTrajectory action service for the arms；GripperCommand service for your gripper.此处仅介绍MoveIt端的相关配置；
- controllers.yaml进行MoveIt端 控制器 配置
- - 对FollowJointTrajectory Controller Interface和GripperCommand Controller Interface进行配置
controller_list:
- name: panda_arm_controller
action_ns: follow_joint_trajectory
type: FollowJointTrajectory
default: true
joints:
- panda_joint1
- panda_joint2
- panda_joint3
- panda_joint4
- panda_joint5
- panda_joint6
- panda_joint7
- name: hand_controller
action_ns: gripper_action
type: GripperCommand
default: true
parallel: true
joints:
- panda_finger_joint1
- panda_finger_joint2
- - Optional Allowed Trajectory Execution Duration Parameters：
allowed_execution_duration_scaling: 1.2
allowed_goal_duration_margin: 0.5
The parameters are used to compute the allowed trajectory execution duration by scaling the expected execution duration and adding the margin afterwards. If this duration is exceeded the trajectory will be cancelled. The controller-specific parameters can be set as follows
- Create the Controller launch file 加载
robot_moveit_controller_manager.launch.xml
- Debugging Information 调试
The FollowJointTrajectory or GripperCommand interfaces on your robot must be communicating in the namespace: /name/action_ns. In the above example, you should be able to see the following topics (using rostopic list) on your robot:
/panda_arm_controller/follow_joint_trajectory/goal ### 格式：/contorller_name/action_ns_name.
/panda_arm_controller/follow_joint_trajectory/feedback
/panda_arm_controller/follow_joint_trajectory/result
/hand_controller/gripper_action/goal
/hand_controller/gripper_action/feedback
/hand_controller/gripper_action/result
- Remapping /joint_states topic 重映射
When you run a move group node, you may need to remap the topic /joint_states to /robot/joint_states, otherwise MoveIt! won’t have feedback from the joints.
- Trajectory Execution Manager Options 轨迹执行管理器 选项
trajectory_execution.launch.xml
1.execution_duration_monitoring: when false, will not throw error is trajectory takes longer than expected to complete at the low-level controller side
2.allowed_goal_duration_margin: Allow more than the expected execution time before triggering a trajectory cancel (applied after scaling)
3.allowed_start_tolerance: Allowed joint-value tolerance for validation that trajectory’s first point matches current robot state. If set to zero will skip waiting for robot to stop after execution
#### Perception Pipeline Tutorial
integration of 3D sensors using Octomap.
配置、集成3D传感器；
The primary component in MoveIt! that deals with 3D perception is the Occupancy Map Updater. The updater uses a plugin architecture to process different types of input. The currently available plugins in MoveIt! are:
1.The PointCloud Occupancy Map Updater: which can take as input point clouds (sensor_msgs/PointCloud2)
2.The Depth Image Occupancy Map Updater: which can take as input Depth Images (sensor_msgs/Image)
- YAML Configuration file (Point Cloud)
“sensors_kinect_pointcloud.yaml”:
sensors:
- sensor_plugin: occupancy_map_monitor/PointCloudOctomapUpdater
point_cloud_topic: /camera/depth_registered/points
max_range: 5.0
point_subsample: 1
padding_offset: 0.1
padding_scale: 1.0
max_update_rate: 1.0
filtered_cloud_topic: filtered_cloud
- YAML Configuration file (Depth Map)
“sensors_kinect_depthmap.yaml”:
sensors:
- sensor_plugin: occupancy_map_monitor/DepthImageOctomapUpdater
image_topic: /camera/depth_registered/image_raw
queue_size: 5
near_clipping_plane_distance: 0.3
far_clipping_plane_distance: 5.0
shadow_threshold: 0.2
padding_scale: 4.0
padding_offset: 0.03
max_update_rate: 1.0
filtered_cloud_topic: filtered_cloud
- Update the launch file
need to update the sensor_manager.launch file
加载：