Table of Contents
Setting up the Bullet world with a new robot
This tutorial will walk you though creating your own repo / metapackage from scratch that will use CRAM and Bullet world with your own robots. In this tutorial we will use the Boxy robot as an example.
The starting point of this tutorial is an installation of CRAM including projection with PR2. If you followed the installation manual, you should have all the necessary packages already.
Robot URDF description
The first thing that we actually need is the robot, more precisely, its URDF description. For Boxy it is located in a repo on Github, so let's clone it into our ROS workspace:
cd ROS_WORKSPACE_FOR_LISP_CODE cd src git clone https://github.com/code-iai/iai_robots.git cd .. catkin_make
CRAM takes the URDF descriptions of the robots from the ROS parameter server, i.e., you will need to upload the URDFs of your robots as a ROS parameter. For Boxy there is a launch file doing that, you will find it here:
roscd iai_boxy_description/launch/ && ls -l
It's called upload_boxy.launch
and has the following contents:
<launch> <arg name="urdf-name" default="boxy_description.urdf.xacro"/> <arg name="urdf-path" default="$(find iai_boxy_description)/robots/$(arg urdf-name)"/> <param name="robot_description" command="$(find xacro)/xacro.py '$(arg urdf-path)'" /> </launch>
As we will need to know the names of the TF frames later, we will launch a general file that includes uploading the URDF as well as a robot state publisher:
roslaunch iai_boxy_description display.launch
(It also starts a GUI to play with the joint angles but let's ignore that.)
Let's check if the URDF's on the parameter server using RViz:
rosrun rviz rviz Add -> RobotModel -> Robot Description: robot_description Add -> TF
To be able to see the TF frames choose base_footprint
as the global fixed frame.
Directory / file setup
Now let's setup a directory structure for our own packages: a directory (repo) and the metapackage inside: in the src
of a catkin workspace create a new directory, we will call it cram_boxy
. Therein create a catkin metapackage with the same name:
mkdir cram_boxy && cd cram_boxy catkin_create_pkg cram_boxy && cd cram_boxy
Edit the CMakeLists.txt
such that it contains only the metapackage boilerplate code:
cmake_minimum_required(VERSION 2.8.3) project(cram_boxy) find_package(catkin REQUIRED) catkin_metapackage()
The first ROS package we will create will be the Prolog description of our robot. We will call it cram_boxy_description
.
Go back to the root of your cram_boxy
directory and create the package. The dependencies we will definitely need for now will be cram_prolog
(as we're defining Prolog rules) and cram_robot_interfaces
(which defines the names of predicates for describing robots in CRAM):
cd ..
catkin_create_pkg cram_boxy_knowledge cram_prolog cram_robot_interfaces
Now let's create the corresponding ASDF file called cram_boxy_knowledge/cram-boxy-knowledge.asd
:
;;; You might want to add a license header first (defsystem cram-boxy-knowledge :author "Your Name" :license "BSD" :depends-on (cram-prolog cram-robot-interfaces) :components ((:module "src" :components ((:file "package") (:file "boxy-knowledge" :depends-on ("package"))))))
Now create the corresponding src
directory and a cram_boxy_knowledge/src/package.lisp
file in it:
;;; license (in-package :cl-user) (defpackage cram-boxy-knowledge (:use #:common-lisp #:cram-prolog #:cram-robot-interfaces))
Also, an empty cram_boxy/cram_boxy_knowledge/src/boxy-knowledge.lisp
.
Now, let's compile our new packages and load them through the REPL:
CL-USER> , ros-load-system cram_boxy_knowledge cram-boxy-knowledge
Boxy Prolog description
Now, let's describe our robot in Prolog, such that we could do some reasoning with it.
We fill in the file cram_boxy/cram_boxy_knowledge/src/boxy-knowledge.lisp
with some simple descriptions of Boxy, which are the ones relevant for navigation and vision. We will leave manipulation out for now as it is too complex for the scope of this tutorial.
As can be seen from the TF tree, our robot has 3 camera frames, 1 depth and 1 RGB frame from a Kinect camera, and an RGB frame from a Kinect2 camera.
It's camera can be from 1.60 m to 2.10 m above the ground, depending on the torso position. It also has a pan-tilt-unit.
;;; license (in-package :cram-boxy-knowledge) (def-fact-group boxy-metadata (robot camera-frame camera-minimal-height camera-maximal-height robot-pan-tilt-links robot-pan-tilt-joints) (<- (robot boxy)) (<- (camera-frame boxy "head_mount_kinect2_rgb_optical_frame")) (<- (camera-frame boxy "shoulder_kinect_rgb_optical_frame")) (<- (camera-frame boxy "shoulder_kinect_depth_optical_frame")) (<- (camera-minimal-height boxy 1.60)) (<- (camera-maximal-height boxy 2.10)) (<- (robot-pan-tilt-links boxy "pw070_box" "pw070_plate")) (<- (robot-pan-tilt-joints boxy "head_pan_joint" "head_tilt_joint")))
Finally, compile the file (Ctrl-c Ctrl-k
).
Loading the world
Now let's try to load our robot also into the Bullet world. We will spawn the floor, the robot, and a couple of household objects.
For that, we
- load the bullet reasoning package in the REPL
- start a ROS node
- spawn the robot and the floor
- spawn a big box for a table and a couple of household objects to go on top
;; step 1 (asdf:load-system :cram-bullet-reasoning) (in-package :btr) ;; step 2 (roslisp:start-ros-node "cram_bullet_boxy") ;; step 3 (let ((robot-urdf (cl-urdf:parse-urdf (roslisp:get-param "robot_description")))) (prolog `(and (clear-bullet-world) (bullet-world ?w) (debug-window ?w) (robot ?robot) (assert (object ?w :static-plane floor ((0 0 0) (0 0 0 1)) :normal (0 0 1) :constant 0 :disable-collisions-with (?robot))) (assert (object ?w :urdf ?robot ((0 0 0) (0 0 0 1)) :urdf ,robot-urdf))))) ;; step 4 (prolog `(and (bullet-world ?w) (assert (object ?w :box table-0 ((2.1 0 0.5) (0 0 0 1)) :size (0.7 1.5 1) :mass 10.0)) (assert (object ?w :mesh pot-0 ((2 0 1.1) (0 0 0 1)) :mass 0.5 :color (0.1 0.2 0.3) :mesh :pot)) (assert (object ?w :mesh mug-0 ((2.2 -0.2 1.07) (0 0 0 1)) :mass 0.2 :color (0.8 0.3 0) :mesh :mug)) (assert (object ?w :mesh mug-1 ((2.3 0 1.07) (0 0 0 1)) :mass 0.2 :color (0.5 0.8 0) :mesh :mug))))
Reasoning with Boxy
Let's try some reasoning:
BTR> (prolog '(visible ?world ?robot pot-0)) NIL
The query asks if the object pot-0
is visible to the robot.
The answer is “No”, as our robot is very tall and look straight ahead.
Now let's put the object higher and try again:
BTR> (prolog '(and (bullet-world ?w) (assert (object-pose ?w pot-0 ((2 0 2) (0 0 0 1)))))) BTR> (prolog '(visible ?world ?robot pot-0)) (((?WORLD . #<BT-REASONING-WORLD {100D78C5F3}>) (?ROBOT . CRAM-BOXY-KNOWLEDGE::BOXY)) . #S(CRAM-UTILITIES::LAZY-CONS-ELEM :GENERATOR #<CLOSURE # {101275A8FB}>))
Now it is visible.
Let's put the pot down:
BTR> (simulate *current-bullet-world* 50)
Now let's do something more complex: let's generate a visibility costmap, that will generate poses from where Boxy will be able to see the pot. As we're going to be using costmaps, we will need to define costmap metadata first:
BTR> (def-fact-group costmap-metadata () (<- (location-costmap:costmap-size 12 12)) (<- (location-costmap:costmap-origin -6 -6)) (<- (location-costmap:costmap-resolution 0.05)) (<- (location-costmap:costmap-padding 0.35)) (<- (location-costmap:costmap-manipulation-padding 0.35)) (<- (location-costmap:costmap-in-reach-distance 1.0)) (<- (location-costmap:costmap-reach-minimal-distance 0.1)))
We should also load the cram_bullet_reasoning_designators
package, as visibility costmap is implemented in it:
BTR> (asdf:load-system :cram-bullet-reasoning-designators)
Now let's create a location designator for a pose to see the mug-0
object, which is the orange mug in the corner, and try to resolve it:
BTR> (let ((location-to-see (desig:make-designator :location '((:to :see) (:object mug-0))))) (desig:reference location-to-see))