3D Simulation in ROS. Mihai Emanuel Dolha Intelligent Autonomous Systems Technische Universität München. November 4, 2010

Transcription

1 in ROS Intelligent Autonomous Systems Technische Universität München

2 Outline 1. Introduction 2. Gazebo 3. Gazebo in ROS 4. Examples

3 Outline 1. Introduction 2. Gazebo 3. Gazebo in ROS 4. Examples

4 Why do we use simulators? (1/2)

5 Why do we use simulators?(2/2)

6 3D Simulator Components

7 3D Simulator Components

8 3D Simulator Components

9 3D Simulator Components

10 Outline 1. Introduction 2. Gazebo 3. Gazebo in ROS 4. Examples

11 Gazebo 3D multi robot simulator with dynamics part of the Player/Stage project

12 Physics Engine(s) currently supported: ODE, Bullet

13 Physics Engine(s) currently supported: ODE, Bullet rigid body dynamics

14 Physics Engine(s) currently supported: ODE, Bullet rigid body dynamics based on Newton s second law: F = m a

15 Physics Engine(s) currently supported: ODE, Bullet rigid body dynamics based on Newton s second law: F = m a constraint formulation

16 Physics Engine(s) currently supported: ODE, Bullet rigid body dynamics based on Newton s second law: F = m a constraint formulation collision detection

17 Physics Engine(s) currently supported: ODE, Bullet rigid body dynamics based on Newton s second law: F = m a constraint formulation collision detection accelerations, velocities and poses

18 Physics Engine(s) Constraints joints contacts Collision detection continuous or discrete broad phase and narrow phase

19 Intro Gazebo Gazebo in ROS Examples Rendering Engine Ogre3D I Object-Oriented Graphics Rendering Engine I based on OpenGL

20 Modelling in Gazebo Gazebo model other models bodies pose,mass geometries collision shape visual shape sensors joints controllers

21 Sensors in Gazebo Laser sensors provided by physics engine raycasting zero sweeping duration noise free real world data is much more cluttered

22 Sensors in Gazebo Cameras provided by rendering engine ideal pinhole cameras noise free and in focus no calibration needed real world like texturing, shading and lighting require effort

23 Modeling in Gazebo World files

24 Communication in Gazebo Controllers and interfaces

25 Communication in Gazebo Controllers and interfaces clients write commands on interfaces

26 Communication in Gazebo Controllers and interfaces clients write commands on interfaces controllers get commands from interfaces

27 Communication in Gazebo Controllers and interfaces clients write commands on interfaces controllers get commands from interfaces commands are processed, then applied to simulated model

28 Communication in Gazebo Controllers and interfaces clients write commands on interfaces controllers get commands from interfaces commands are processed, then applied to simulated model current model status and results are send to client

29 Outline 1. Introduction 2. Gazebo 3. Gazebo in ROS 4. Examples

30 Overview stack: simulator_gazebo actively maintained and developed improved modeling mechanism integrated in the ROS comunication mechanisms

31 Modeling using URDF URDF Description: <robot name= " t e s t _ r o b o t "> < l i n k name= " l i n k 1 " / > < l i n k name= " l i n k 2 " / > < l i n k name= " l i n k 3 " / > < l i n k name= " l i n k 4 " / > < j o i n t name= " j o i n t 1 " type= " continuous " > <parent l i n k = " l i n k 1 " / > < c h i l d l i n k = " l i n k 2 " / > < / j o i n t > < j o i n t name= " j o i n t 2 " type= " continuous " > <parent l i n k = " l i n k 1 " / > < c h i l d l i n k = " l i n k 3 " / > < / j o i n t > < j o i n t name= " j o i n t 3 " type= " continuous " > <parent l i n k = " l i n k 3 " / > < c h i l d l i n k = " l i n k 4 " / > < / j o i n t > < / robot>

32 Modeling Gazebo URDF extension <gazebo reference=" f i n g e r _ t i p _ c a m e r a _ l i n k " > <sensor:camera name= " finger_tip_camera_sensor "> <imagesize> < / imagesize> <imageformat>l8< / imageformat> <hfov>90< / hfov> < nearclip>0.01< / nearclip> < farclip >100< / farclip > <updaterate>20.0< / updaterate> < c o n t r o l l e r :r o s _c a m e r a name= " f i n g e r _ t i p _ c a m e r a _ c o n t r o l l e r " p l u g i n = " libros_camera. so "> <alwayson> t r u e < / alwayson> <updaterate>20.0< / updaterate> <topicname>finger_tip_cam / image< / topicname> <framename> f i n g e r _tip_camera_link< / framename> < i n t e r f a c e : c a m e r a name= " f i n g e r _ t i p _ c a m e r a _ i f a c e " / > < / c o n t r o l l e r :ros_camera> < / sensor:camera> < t u r n G r a v i t y O f f > t r u e < / t u r n G r a v i t y O f f > < m a t e r i a l >PR2/ Blue< / m a t e r i a l > < / gazebo>

33 Modeling Loading a URDF model in Gazebo <launch> <! send pr2 urdf to param server > <param name= " robot_ description " command= " $( find xacro ) / xacro. py $( find p r 2 _ d e s c r i p t i o n ) / robots / pr2. u r d f. xacro " / > <! push robot_ description to factory and spawn robot in gazebo > <node name= " pr2_gazebo_model " pkg= " gazebo " type= " spawn_model " args= " $( optenv ROBOT_INITIAL_POSE ) unpause urdf param robot_ description model pr2 " respawn= " false " output=" screen " / > < / launch>

34 Communication & Control

35 Communication & Control robot description on parameter server

36 Communication & Control robot description on parameter server the controller manager:

37 Communication & Control robot description on parameter server the controller manager: loads controllers

38 Communication & Control robot description on parameter server the controller manager: loads controllers creates a robot state object

39 Communication & Control robot description on parameter server the controller manager: loads controllers creates a robot state object client nodes publish their commands on topics

40 Communication & Control robot description on parameter server the controller manager: loads controllers creates a robot state object client nodes publish their commands on topics controllers read the topics, process the command and push it to the robot state

41 Communication & Control robot description on parameter server the controller manager: loads controllers creates a robot state object client nodes publish their commands on topics controllers read the topics, process the command and push it to the robot state the controller manager gets the commands from the robot state and sends them to the hardware or to the simulated model

42 Communication & Control pr2_teleop publishes commands on topic (/base_contrller/command) base_controller computes commands for each wheel and updates the commands on the robot state the gazebo_ros_controller_manager checks the robot state for commands and sends them to the joints of the simulated model for controlling the real hardware: pr2_controller_manager real world / simulator switching is done by the env. var. ROBOT

43 Outline 1. Introduction 2. Gazebo 3. Gazebo in ROS 4. Examples

44 The PR2 pluging in

45 Naive physics simulation

46 Naive physics simulation

47 Human character simulation

48 Thank you Questions?