Multi-Robot Systems with ROS Lesson 8

Multi-Robot Systems with ROS Lesson 8

Teaching Assistant: Roi [email protected]

Summer 2015

mailto:[email protected]

(C)2014 Roi Yehoshua

Agenda• TAO events• Allocating sub-plans• Defining custom Next protocols• Wandering robot example


TAO Events• TAO defines an event distribution system using

an EventQueue• It’s used for sharing events inside TAO machines• It’s possible to insert external events to the

system (from ROS or other custom source)• It is thread safe


TAO Event• Each Event is a path containing:– all context names– when this event was created– an event short name at the end

• Example: /ContextName/EventName • When you compare two events you can use

regular expressions as the name of one event by writing @ at the beggining of the name. – Example: @/Con.*/Event[NT]...e


Events Inside TAO• TAO_RAISE(/STOP) - raise global event• TAO_RAISE(STOP) - raise an event related to TAO

context • TAO_RAISE(PLAN_NAME/STOP) - raise an event

related to TAO PLAN context event• TAO_STOP_CONDITION(event==TAO_EVENT(STOP))

- check condition based on an occurred event• TAO_EVENTS_DROP - Clear current events queue


Events Outside TAO• Defining an event:– Event e("/STOP") - global / without context– Event e("STOP",call_context) - related to call_context

• Raising the event:– events->raiseEvent(e);


Events Interface• Event waitEvent() - block function until a new

event arrives• Event tryGetEvent(bool& success) - get a new

event if exists (non-blocking call)• bool isTerminated() const - check if the event

system is closed• void drop_all() -


Events InterfaceFunction

Block function until a new event arrives Event waitEvent )(Get a new event if exists (non-blocking call) Event tryGetEvent(bool&

success) Check if the event system is closed bool isTerminated)(Clear queue void drop_all)(Close event system, releasing all waiting processes void close)(

Send one /SPIN event for validation of STOP conditions

spinOne)(

Run spinOne() command with rate_in_hz spin(double rate_in_hz = 10)

Run spin command after start_delay without blocking current code execution

async_spin(double rate_in_hz = 10, double start_delay=0)


RosEventQueue• A class derived from decision_making::EventQueue• RosEventQueue creates a connection between ROS

(/decision_making/NODE_NAME/events topic) and the internal EventQueue

• Must be created after ros::init and ros_decision_making_init


Events Example• In the following example, we will add a support

for a STOP event to our Incrementer plan• Copy TaskWithStopCondition.cpp to Events.cpp• In the TAO machine definition, add a clause to

the STOP condition that checks if a STOP event has occurred


TaoEvents.cppTAO(Incrementer){ TAO_PLANS { Increment } TAO_START_PLAN(Increment); TAO_BGN { TAO_PLAN(Increment) { TAO_START_CONDITION(true); TAO_CALL_TASK(incrementTask); TAO_ALLOCATE_EMPTY TAO_STOP_CONDITION(WM.counter == 100 || event == TAO_EVENT("/STOP")); TAO_NEXT_EMPTY } } TAO_END}


Sending Events• Once running, your model will be able to receive

events over the decision_making/[NODE_NAME]/events topic

• Events to the model can be sent using:

• For example, to send a STOP event to the tao_events node, type:

$ rostopic pub decision_making/[NODE_NAME]/events std_msgs/String "EVENT_NAME"

rostopic pub decision_making/tao_events/events std_msgs/String "STOP"


Sending Events Example


Allocating SubPlans• We will now change the incrementer plan so it

allocates two sub-plans:– Even – this subplan will increment the counter when

it has an even value– Odd – this subplan will increment the counter when it

has an odd value• Copy BasicPlanWithWM.cpp to

AllocatingSubPlans.cpp


AllocatingSubPlans.cpp (1)struct WorldModel : public CallContextParameters { int counter; bool even_plan_finished; bool odd_plan_finished; string str() const { stringstream s; s << "counter = " << counter; return s.str(); }};#define WM TAO_CONTEXT.parameters<WorldModel>()


AllocatingSubPlans.cpp (2)TAO_HEADER(Even)TAO_HEADER(Odd) TAO(Incrementer){ TAO_PLANS { Increment } TAO_START_PLAN(Increment); TAO_BGN { TAO_PLAN(Increment) { TAO_START_CONDITION(WM.counter < 100); WM.even_plan_finished = false; WM.odd_plan_finished = false; TAO_ALLOCATE(AllocFirstReady) { TAO_SUBPLAN(Even); TAO_SUBPLAN(Odd); } TAO_STOP_CONDITION(WM.even_plan_finished || WM.odd_plan_finished); TAO_NEXT(NextFirstReady) { TAO_NEXT_PLAN(Increment); } } } TAO_END}


AllocatingSubPlans.cpp (3)TAO(Even){ TAO_PLANS { Even, } TAO_START_PLAN(Even); TAO_BGN { TAO_PLAN(Even) { TAO_START_CONDITION(WM.counter % 2 == 0); WM.counter++; cout << "Even: " << WM.str() << endl; boost::this_thread::sleep(boost::posix_time::milliseconds(100)); TAO_ALLOCATE_EMPTY TAO_STOP_CONDITION(true); TAO_NEXT_EMPTY WM.even_plan_finished = true; } } TAO_END}


AllocatingSubPlans.cpp (4)TAO(Odd){ TAO_PLANS{ Odd, } TAO_START_PLAN(Odd); TAO_BGN { TAO_PLAN(Odd) { TAO_START_CONDITION(WM.counter % 2 == 1); WM.counter++; cout << "Odd: " << WM.str() << endl; boost::this_thread::sleep(boost::posix_time::milliseconds(100)); TAO_ALLOCATE_EMPTY TAO_STOP_CONDITION(true); TAO_NEXT_EMPTY WM.odd_plan_finished = true; } } TAO_END}


SubPlans Behavior• The sub-plans start executing only after the parent plan

reaches its stop condition (and not right after allocation)• If the parent’s stop condition is true before any of its

sub-plans started running, then the TAO machine ends• If the parent’s stop condition is false and the parent’s

plan has a next plan, then it is unpredictable whether the next plan or the sub-plan starts first

• Once a plan starts executing, no other plan can execute at the same time (unless using tasks)

• The entire TAO machine ends only when the parent plan and all its sub-plans are finished


Allocating SubPlans Demo


Decision Graph


Wandering Robot Plan• Now we will write a TAO plan for a wandering robot• The wandering plan will be composed of two sub-

plans:– Drive – makes the robot drive forward until an obstacle is

detected– Turn – makes the robot turn until the way becomes clear

• Create a new package called tao_wandering:$ cd ~/dmw/src$ catkin_create_pkg tao_wandering roscpp decision_making decision_making_parser random_numbers sensor_msgs std_msgs geometry_msgs


Wandering.cpp (1)#include <iostream> #include <ros/ros.h>#include <random_numbers/random_numbers.h>#include <sensor_msgs/LaserScan.h>#include <geometry_msgs/Twist.h> #include <decision_making/TAO.h>#include <decision_making/TAOStdProtocols.h>#include <decision_making/ROSTask.h>#include <decision_making/DecisionMaking.h> using namespace std;using namespace decision_making;


Wandering.cpp (2)/*** Constants ***/#define MIN_SCAN_ANGLE_RAD -45.0/180*M_PI#define MAX_SCAN_ANGLE_RAD +45.0/180*M_PI#define MIN_DIST_TO_OBSTACLE 0.8 // in meters /*** Variables ***/random_numbers::RandomNumberGenerator _randomizer;ros::Publisher _velocityPublisher; /*** World model ***/struct WorldModel : public CallContextParameters { bool obstacleDetected; bool driveFinished; bool turnFinished; string str() const { stringstream s; s << "obstacleDetected = " << obstacleDetected; return s.str(); }};#define WM TAO_CONTEXT.parameters<WorldModel>()


Wandering.cpp (3)/*** TAO machine ***/TAO_HEADER(Drive)TAO_HEADER(Turn)

TAO(Wandering){ TAO_PLANS { Wandering } TAO_START_PLAN(Wandering); TAO_BGN { TAO_PLAN(Wandering) { TAO_START_CONDITION(true); WM.driveFinished = false; WM.turnFinished = false; TAO_ALLOCATE(AllocFirstReady) { TAO_SUBPLAN(Drive); TAO_SUBPLAN(Turn); } TAO_STOP_CONDITION(WM.driveFinished || WM.turnFinished); TAO_NEXT(NextFirstReady) { TAO_NEXT_PLAN(Wandering); } } } TAO_END}


Wandering.cpp (4)TAO(Drive){ TAO_PLANS { Drive, } TAO_START_PLAN(Drive); TAO_BGN { TAO_PLAN(Drive) { TAO_START_CONDITION(!WM.obstacleDetected); TAO_CALL_TASK(driveTask); TAO_ALLOCATE_EMPTY TAO_STOP_CONDITION(WM.obstacleDetected); TAO_NEXT_EMPTY WM.driveFinished = true; } } TAO_END}


Wandering.cpp (5)TAO(Turn){ TAO_PLANS{ Turn, } TAO_START_PLAN(Turn); TAO_BGN { TAO_PLAN(Turn) { TAO_START_CONDITION(WM.obstacleDetected); TAO_CALL_TASK(turnTask); TAO_ALLOCATE_EMPTY TAO_STOP_CONDITION(true); TAO_NEXT_EMPTY WM.turnFinished = true; } } TAO_END}


Wandering.cpp (6)/*** Task implementations ***/TaskResult driveTask(string name, const CallContext& context, EventQueue& eventQueue) { ROS_INFO("Driving..."); geometry_msgs::Twist forwardMessage; forwardMessage.linear.x = 1.0; // Preemptive wait while (!eventQueue.isTerminated()) { _velocityPublisher.publish(forwardMessage); boost::this_thread::sleep(boost::posix_time::milliseconds(100.0)); } ROS_INFO("Obstacle detected!"); return TaskResult::SUCCESS();}


Wandering.cpp (7)TaskResult turnTask(string name, const CallContext& context, EventQueue& eventQueue) { ROS_INFO("Turning..."); bool turnLeft = _randomizer.uniformInteger(0, 1); geometry_msgs::Twist turnMessage; turnMessage.angular.z = 2 * (turnLeft ? 1 : -1); int timeToTurnMs = _randomizer.uniformInteger(2000, 4000); int turnLoops = timeToTurnMs / 100; for (int i = 0; i < turnLoops; i++) { _velocityPublisher.publish(turnMessage); boost::this_thread::sleep(boost::posix_time::milliseconds(100.0)); } return TaskResult::SUCCESS();}


Wandering.cpp (8)/*** ROS Subscriptions ***/void onLaserScanMessage(const sensor_msgs::LaserScan::Ptr laserScanMessage, CallContext* context) { bool obstacleFound = false; int minIndex = ceil((MIN_SCAN_ANGLE_RAD - laserScanMessage->angle_min) / laserScanMessage->angle_increment); int maxIndex = floor((MAX_SCAN_ANGLE_RAD - laserScanMessage->angle_min) / laserScanMessage->angle_increment); for (int i = minIndex; i <= maxIndex; i++) { if (laserScanMessage->ranges[i] < MIN_DIST_TO_OBSTACLE) { obstacleFound = true; } } context->parameters<WorldModel>().obstacleDetected = obstacleFound;}


Wandering.cpp (9)int main(int argc, char **argv){ ros::init(argc, argv, "wandering_node"); ros::NodeHandle nh; ros_decision_making_init(argc, argv); // ROS spinner for topic subscriptions ros::AsyncSpinner spinner(1); spinner.start(); // Tasks registration LocalTasks::registrate("driveTask", driveTask); LocalTasks::registrate("turnTask", turnTask); RosEventQueue eventQueue; CallContext context; context.createParameters(new WorldModel());


Wandering.cpp (10) // CallContext must define a team teamwork::SharedMemory db; teamwork::Teammates teammates; teamwork::Team main_team = teamwork::createMainTeam(db, "main", teammates); context.team(TAO_CURRENT_TEAM_NAME, main_team.ptr()); // Subscription for the laser topic and velocity publisher creation ros::Subscriber laserSubscriber = nh.subscribe<void>("base_scan", 1, boost::function<void(const sensor_msgs::LaserScan::Ptr)>(boost::bind(onLaserScanMessage, _1, &context))); _velocityPublisher = nh.advertise<geometry_msgs::Twist>("cmd_vel", 100); eventQueue.async_spin(); ROS_INFO("Starting wandering machine..."); TaoWandering(&context, &eventQueue); eventQueue.close(); ROS_INFO("TAO finished."); return 0;}


Wandering Launch File• Copy worlds directory from

~/catkin_ws/src/gazebo_navigation_multi package• Create a launch directory in the tao_wandering

package• Add the following wandering.launch file


Wandering Launch File

<launch> <master auto="start"/> <param name="/use_sim_time" value="true"/>  <include file="$(find gazebo_ros)/launch/empty_world.launch"> <arg name="world_name" value="$(find tao_wandering)/worlds/willowgarage.world" /> </include> <param name="robot_description" command="$(find xacro)/xacro.py $(find lizi_description)/urdf/lizi.urdf"/> <node name="spawn_urdf" pkg="gazebo_ros" type="spawn_model" args="-x 34 -y 18 -z 0 -Y 1.57 -urdf -param robot_description -model lizi1" output="screen"/> <node name="wandering" pkg="tao_wandering" type="wandering_node" output="screen" />

</launch>


Wandering Demo


Custom Next Protocol• To define your own next protocol:– Create a class that inherits from

decision_making::ProtocolNext– Implement the pure virtual function decide()– Call setDecision at the end of the function with the

chosen plan ID


Custom Next Protocol• In the following example, we will decompose the

Turn plan into TurnLeft and TurnRight subplans• We will create a custom RandomNext protocol

that will randomly choose the next plan from its set of candidate plans

• We will use this protocol to make the Turn plan randomly choose between TurnLeft and TurnRight as its continuation plan


RandomNext Classclass NextRandom: public decision_making::ProtocolNext {public: NextRandom(int& res, decision_making::CallContext* call_context, decision_making::EventQueue* events):ProtocolNext(res, call_context, events){} bool decide(){ vector<int> ready_index; for(size_t i = 0; i < options.size(); i++) if (options[i].isReady) ready_index.push_back(i); if (ready_index.size() == 0) return false; int i = _randomizer.uniformInteger(0, ready_index.size() - 1); return setDecision(options[ready_index[i]].id); }};


Turn Plan (1)TAO(Turn){ TAO_PLANS{ Turn, TurnLeft, TurnRight } TAO_START_PLAN(Turn); TAO_BGN { TAO_PLAN(Turn) { TAO_START_CONDITION(WM.obstacleDetected); TAO_ALLOCATE_EMPTY TAO_STOP_CONDITION(true); TAO_NEXT(NextRandom) { TAO_NEXT_PLAN(TurnLeft); TAO_NEXT_PLAN(TurnRight); } }


Turn Plan (2) TAO_PLAN(TurnLeft) { TAO_START_CONDITION(true); TAO_ALLOCATE_EMPTY; WM.turnLeft = false; TAO_CALL_TASK(turnTask); TAO_STOP_CONDITION(true); TAO_NEXT_EMPTY; WM.turnFinished = true; } TAO_PLAN(TurnRight) { TAO_START_CONDITION(true); TAO_ALLOCATE_EMPTY; WM.turnLeft = true; TAO_CALL_TASK(turnTask); TAO_STOP_CONDITION(true); TAO_NEXT_EMPTY; WM.turnFinished = true; } } TAO_END}


• Add a boolean variable to the world model indicating which turn direction was chosen:

World Model Changes

struct WorldModel : public CallContextParameters { bool obstacleDetected; bool driveFinished; bool turnFinished; bool turnLeft; string str() const { stringstream s; s << "obstacleDetected = " << obstacleDetected; return s.str(); }};#define WM TAO_CONTEXT.parameters<WorldModel>()


• Make the following changes to the turnTask callback:

Turn Task

TaskResult turnTask(string name, const CallContext& context, EventQueue& eventQueue) { if (context.parameters<WorldModel>().turnLeft) ROS_INFO("Turning left..."); else ROS_INFO("Turning right..."); geometry_msgs::Twist turnMessage; turnMessage.angular.z = 2 * (context.parameters<WorldModel>().turnLeft ? 1 : -1); int timeToTurnMs = _randomizer.uniformInteger(2000, 4000); int turnLoops = timeToTurnMs / 100; for (int i = 0; i < turnLoops; i++) { _velocityPublisher.publish(turnMessage); boost::this_thread::sleep(boost::posix_time::milliseconds(100.0)); } return TaskResult::SUCCESS();}


Wandering Demo


Homework (not for submission)• Create a custom next protocol for the turn plan that

will choose between the following 3 plans:– Turn random when there is an obstacle on the front– Turn left when there is an obstacle on the right side– Turn right when there is an obstacle on the left side

• Add a support for pausing/resuming the robot by sending an appropriate event

Date post:	23-Feb-2016
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Multi-Robot Systems with ROS Lesson 8

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