/ros_htn

Primary LanguageC++Apache License 2.0Apache-2.0

ROS_HTN

ros_htn is a Hierarchical Tasks Planner for the Robotic Operative System (ROS). ros_htn contains the functionality needed to solve planning problems in PDDL 2.1 using the HPDL extension [Castillo2006] in a ROS nodes architecture. ros_htn contains 2 nodes: plan_service_node the ros service responsible for calling the HTN planner and return a plan, and domain_updater_node the node used to update the planner's domain.

Table of Contents

  1. Requirements
  2. Installation
  3. Usage
  4. References

Requirements

  • Ubuntu 16.04
  • ROS Kinetic Kame
  • GCC with C++11

Installation

Starting in a ROS Workspace folder, type:

cd src/
git clone https://github.com/Leontes/ros_htn.git
cd ..
rosdep install --from-paths src --ignore-src -r -y
catkin_make

Usage

ROS_HTN comes with a launch file ready to be executed and used. This launch will execute ros_core and the plan_service and domain_updater nodes when used setting as default domain a domain passed as the launch argument. If no planning domain is given ros_htn will use by default the domain.pddl file located in the planningfiles folder. When passing a new domain as input you must provide the full path to the new file in order to make ros_htn correctly set the new domain file. The domain_updater node is subscribed to the /dom_updater topic to receive new domains. Launch file can be executed from the command line as follows:

roslaunch ros_htn htn_server.launch domain:="pathtodomain/newdomain.pddl"

To send a planning problem to the planning server it must be properly formatted. This format is defined in the PlanningProblem.msg file stored in msg folder and consists of 3 parts: the world's objects definition, the initial state of the world and a goal. World's objects are defined as an array of pairs <object, type>. The initial state is defined as a list of logic statements in PDDL [McDermont1998] format. In PDDL boolean logic statements (fluents) are defined as (predicate object1 ... objectN) and numeric logic statements (functions) as ((fluent) value). Finally, the goal of a problem is a list of tasks that must be solved. This tasks must be also written in PDDL format as (task_name argument1 ... argumentN). The file planner_test_client.cpp contains a test example problem for the domain contained in the planningfiles folder. It can be executed by running the node planner_test_client of the ros_htn package.

In planner_test_client.cpp we can see perfectly differentiated the definition of the three components of a planning domain. Such as the objects definition:

ros_htn::PlanningProblem problem;

ros_htn::Object obj;
std::vector<ros_htn::Object> objectsVec;

obj.objName = "general";
obj.objType = "lander";
objectsVec.push_back(obj);

obj.objName = "rover0";
obj.objType = "rover";
objectsVec.push_back(obj);

obj.objName = "rover0store";
obj.objType = "store";
objectsVec.push_back(obj);

obj.objName = "waypoint0";
obj.objType = "waypoint";
objectsVec.push_back(obj);

obj.objName = "waypoint1";
obj.objType = "waypoint";
objectsVec.push_back(obj);

obj.objName = "waypoint2";
obj.objType = "waypoint";
objectsVec.push_back(obj);

obj.objName = "camera0";
obj.objType = "camera";
objectsVec.push_back(obj);

obj.objName = "objective0";
obj.objType = "objective";
objectsVec.push_back(obj);

problem.objects = objectsVec;

The initial state construction:

std::vector<std::string> state;

state.push_back("(at_soil_sample waypoint1)");
state.push_back("(at_rock_sample waypoint2)");
state.push_back("(visible_from objective0 waypoint2)");
state.push_back("(calibration_target camera0 objective0)");
state.push_back("(in_sun waypoint2)");
state.push_back("(at_lander general waypoint0)");
state.push_back("(channel_free general)");
state.push_back("(visible waypoint0 waypoint1)");
state.push_back("(visible waypoint0 waypoint2)");
state.push_back("(store_of rover0store rover0)");
state.push_back("(empty rover0store)");
state.push_back("(equipped_for_rock_analysis rover0)");
state.push_back("(equipped_for_soil_analysis rover0)");
state.push_back("(equipped_for_imaging rover0)");
state.push_back("(visible waypoint1 waypoint2)");
state.push_back("(on_board camera0 rover0)");
state.push_back("(supports camera0 colour)");
state.push_back("(supports camera0 high_res)");
state.push_back("(supports camera0 low_res)");
state.push_back("(= (energy rover0) 5000)");
state.push_back("(= (recharge-rate rover0) 5)");
state.push_back("(at rover0 waypoint0)");
state.push_back("(available rover0)");
state.push_back("(can_traverse rover0 waypoint0 waypoint1)");
state.push_back("(can_traverse rover0 waypoint0 waypoint2)");
state.push_back("(can_traverse rover0 waypoint1 waypoint2)");

problem.initState = state;

And the goal tasks addition:

std::vector<std::string> tasks;

tasks.push_back("(sample rover0 waypoint1)");
tasks.push_back("(sample rover0 waypoint2)");
tasks.push_back("(photo rover0 objective0 high_res)");

problem.goal = tasks;

References

Castillo2006: Castillo, L. A., Fernández-Olivares, J., Garcia-Perez, O., & Palao, F. (2006, June). Efficiently Handling Temporal Knowledge in an HTN Planner. In ICAPS (pp. 63-72).

McDermott1998: McDermott, D., Ghallab, M., Howe, A., Knoblock, C., Ram, A., Veloso, M., Weld, D. and Wilkins, D. (1998). PDDL-the planning domain definition language.Technical Report CVC TR98-003/DCS TR-1165, Yale Center for Computational Vision and Control.