auto result = task.execute(*task.solutions().front());
if (result.val != moveit_msgs::msg::MoveItErrorCodes::SUCCESS){
RCLCPP_ERROR_STREAM(LOGGER, "Task execution failed");
return;
}
mtc::Stage* current_state_ptr = nullptr; // Forward current_state on to grasp pose generator
pragma GCC diagnostic pop
/****************************************************
* *
* Current State *
* *
***************************************************/
auto stage_state_current = std::make_unique("current");
current_state_ptr = stage_state_current.get();
task.add(std::move(stage_state_current));
auto sampling_planner = std::makeshared(node);
auto interpolation_planner = std::make_shared();
auto cartesian_planner = std::make_shared();
cartesian_planner->setMaxVelocityScalingFactor(1.0);
cartesian_planner->setMaxAccelerationScalingFactor(1.0);
cartesian_planner->setStepSize(.01);
/****************************************************
* *
* Open Hand *
* *
***************************************************/
mtc::Stage* initial_state_ptr = nullptr;
{
auto stage_open_hand =
std::make_unique("open hand", interpolation_planner);
stage_open_hand->setGroup(hand_group_name);
stage_open_hand->setGoal("open");
initial_state_ptr = stage_open_hand.get(); // remember start state for monitoring grasp pose generator
task.add(std::move(stage_open_hand));
}
I'm trying to do this tutorial: https://moveit.picknik.ai/main/doc/tutorials/pick_and_place_with_moveit_task_constructor/pick_and_place_with_moveit_task_constructor.html
After some tries with the code provided in the tutorial and finding some errors, I've tried to complete the code with this code (which is the one that at the beginning of the tutorial is used as an example): https://github.com/moveit/moveit_task_constructor/blob/master/demo/src/pick_place_task.cpp
This is the result code mtc_node_panda.cpp:
include <rclcpp/rclcpp.hpp>
include <moveit/planning_scene/planning_scene.h>
include <moveit/planning_scene_interface/planning_scene_interface.h>
include <moveit/task_constructor/task.h>
include <moveit/task_constructor/solvers.h>
include <moveit/task_constructor/stages.h>
if __has_include(<tf2_geometry_msgs/tf2_geometry_msgs.hpp>)
include <tf2_geometry_msgs/tf2_geometry_msgs.hpp>
else
include <tf2_geometry_msgs/tf2_geometry_msgs.h>
endif
if __has_include(<tf2_eigen/tf2_eigen.hpp>)
include <tf2_eigen/tf2_eigen.hpp>
else
include <tf2_eigen/tf2_eigen.h>
endif
static const rclcpp::Logger LOGGER = rclcpp::get_logger("mtc_tutorial"); namespace mtc = moveit::task_constructor;
class MTCTaskNode{ public: MTCTaskNode(const rclcpp::NodeOptions& options);
rclcpp::node_interfaces::NodeBaseInterface::SharedPtr getNodeBaseInterface();
void doTask();
void setupPlanningScene();
private: // Compose an MTC task from a series of stages. mtc::Task createTask(); mtc::Task task; rclcpp::Node::SharedPtr node; };
MTCTaskNode::MTCTaskNode(const rclcpp::NodeOptions& options) : node_{ std::make_shared("mtc_node", options) }
{
}
rclcpp::nodeinterfaces::NodeBaseInterface::SharedPtr MTCTaskNode::getNodeBaseInterface(){ return node->get_node_base_interface(); }
void MTCTaskNode::setupPlanningScene(){ moveit_msgs::msg::CollisionObject object; object.id = "object"; object.header.frame_id = "world"; object.primitives.resize(1); object.primitives[0].type = shape_msgs::msg::SolidPrimitive::CYLINDER; object.primitives[0].dimensions = { 0.1, 0.02 };
geometry_msgs::msg::Pose pose; pose.position.x = 0.5; pose.position.y = -0.25; pose.position.z = 0.05; pose.orientation.w = 1.0; object.pose = pose;
moveit::planning_interface::PlanningSceneInterface psi; psi.applyCollisionObject(object); }
void MTCTaskNode::doTask() { task_ = createTask();
try{ task_.init(); } catch (mtc::InitStageException& e){ RCLCPP_ERROR_STREAM(LOGGER, e); return; }
if (!task_.plan(5)){ RCLCPP_ERROR_STREAM(LOGGER, "Task planning failed"); return; }
task.introspection().publishSolution(*task.solutions().front());
auto result = task.execute(*task.solutions().front()); if (result.val != moveit_msgs::msg::MoveItErrorCodes::SUCCESS){ RCLCPP_ERROR_STREAM(LOGGER, "Task execution failed"); return; }
return; }
mtc::Task MTCTaskNode::createTask() { mtc::Task task; task.stages()->setName("demo task"); task.loadRobotModel(node_);
const auto& arm_group_name = "panda_arm"; const auto& hand_group_name = "hand"; const auto& hand_frame = "panda_hand";
// Set task properties task.setProperty("group", arm_group_name); task.setProperty("eef", hand_group_name); task.setProperty("ik_frame", hand_frame);
// Disable warnings for this line, as it's a variable that's set but not used in this example
pragma GCC diagnostic push
pragma GCC diagnostic ignored "-Wunused-but-set-variable"
pragma GCC diagnostic pop
auto stage_state_current = std::make_unique("current");
current_state_ptr = stage_state_current.get();
task.add(std::move(stage_state_current));
auto sampling_planner = std::makeshared(node );
auto interpolation_planner = std::make_shared();
auto cartesian_planner = std::make_shared();
cartesian_planner->setMaxVelocityScalingFactor(1.0);
cartesian_planner->setMaxAccelerationScalingFactor(1.0);
cartesian_planner->setStepSize(.01);
mtc::Stage* initial_state_ptr = nullptr; { auto stage_open_hand = std::make_unique("open hand", interpolation_planner);
stage_open_hand->setGroup(hand_group_name);
stage_open_hand->setGoal("open");
initial_state_ptr = stage_open_hand.get(); // remember start state for monitoring grasp pose generator
task.add(std::move(stage_open_hand));
}
{ auto stage_move_to_pick = std::make_unique(
"move to pick",
mtc::stages::Connect::GroupPlannerVector{ { arm_group_name, sampling_planner } });
stage_move_to_pick->setTimeout(5.0);
stage_move_to_pick->properties().configureInitFrom(mtc::Stage::PARENT);
task.add(std::move(stage_move_to_pick));
}
mtc::Stage* attach_object_stage = nullptr; // Forward attach_object_stage to place pose generator { auto grasp = std::make_unique("pick object");
task.properties().exposeTo(grasp->properties(), { "eef", "group", "ik_frame" });
grasp->properties().configureInitFrom(mtc::Stage::PARENT,{ "eef", "group", "ik_frame" });
}
{ auto stage_move_to_place = std::make_unique(
"move to place",
mtc::stages::Connect::GroupPlannerVector{ { arm_group_name, sampling_planner },
{ hand_group_name, interpolation_planner } });
stage_move_to_place->setTimeout(5.0);
stage_move_to_place->properties().configureInitFrom(mtc::Stage::PARENT);
task.add(std::move(stage_move_to_place));
}
{ auto place = std::make_unique("place object");
task.properties().exposeTo(place->properties(), { "eef", "group", "ik_frame" });
place->properties().configureInitFrom(mtc::Stage::PARENT, { "eef", "group", "ik_frame" });
}
{ auto stage = std::make_unique("return home", interpolation_planner);
stage->properties().configureInitFrom(mtc::Stage::PARENT, { "group" });
stage->setGoal("ready");
task.add(std::move(stage));
}
return task; }
int main(int argc, char** argv) { rclcpp::init(argc, argv);
rclcpp::NodeOptions options; options.automatically_declare_parameters_from_overrides(true);
auto mtc_task_node = std::make_shared(options);
rclcpp::executors::MultiThreadedExecutor executor;
auto spin_thread = std::make_unique([&executor, &mtc_task_node]() {
executor.add_node(mtc_task_node->getNodeBaseInterface());
executor.spin();
executor.remove_node(mtc_task_node->getNodeBaseInterface());
});
mtc_task_node->setupPlanningScene(); mtc_task_node->doTask();
spin_thread->join(); rclcpp::shutdown(); return 0; }
And the logs I receive (I've already tried with lower values of cartesian Step Size and same result):
luki@luki-Lenovo-B50-80:~/ws_moveit2$ ros2 launch mtc_tutorial_panda pick_place_demo.launch.py [INFO] [launch]: All log files can be found below /home/luki/.ros/log/2024-05-29-21-14-02-699214-luki-Lenovo-B50-80-15255 [INFO] [launch]: Default logging verbosity is set to INFO [INFO] [mtc_node_panda-1]: process started with pid [15258] [mtc_node_panda-1] [INFO] [1717010043.873541429] [planning_scene_interface_108803162633264.moveit.RDFLoader]: Loaded robot model in 0.00762448 seconds [mtc_node_panda-1] [INFO] [1717010043.873783262] [planning_scene_interface_108803162633264.moveit.robot_model]: Loading robot model 'panda'... [mtc_node_panda-1] [INFO] [1717010043.943075838] [planning_scene_interface_108803162633264.moveit.kdl_kinematics_plugin]: Joint weights for group 'panda_arm': 1 1 1 1 1 1 1 [mtc_node_panda-1] [INFO] [1717010044.129018848] [planning_scene_interface_108803162633264.moveit.planning_pipeline]: Successfully loaded planner 'OMPL' [mtc_node_panda-1] [INFO] [1717010044.147246651] [mtc_node]: Try loading adapter 'default_planning_request_adapters/ResolveConstraintFrames' [mtc_node_panda-1] [INFO] [1717010044.150986068] [mtc_node]: Loaded adapter 'default_planning_request_adapters/ResolveConstraintFrames' [mtc_node_panda-1] [INFO] [1717010044.151051695] [mtc_node]: Try loading adapter 'default_planning_request_adapters/ValidateWorkspaceBounds' [mtc_node_panda-1] [INFO] [1717010044.152187358] [mtc_node]: Loaded adapter 'default_planning_request_adapters/ValidateWorkspaceBounds' [mtc_node_panda-1] [INFO] [1717010044.152263498] [mtc_node]: Try loading adapter 'default_planning_request_adapters/CheckStartStateBounds' [mtc_node_panda-1] [INFO] [1717010044.152413553] [mtc_node]: Loaded adapter 'default_planning_request_adapters/CheckStartStateBounds' [mtc_node_panda-1] [INFO] [1717010044.152442319] [mtc_node]: Try loading adapter 'default_planning_request_adapters/CheckStartStateCollision' [mtc_node_panda-1] [INFO] [1717010044.152485459] [mtc_node]: Loaded adapter 'default_planning_request_adapters/CheckStartStateCollision' [mtc_node_panda-1] [INFO] [1717010044.169735655] [mtc_node]: Try loading adapter 'default_planning_response_adapters/AddTimeOptimalParameterization' [mtc_node_panda-1] [INFO] [1717010044.180261330] [mtc_node]: Loaded adapter 'default_planning_response_adapters/AddTimeOptimalParameterization' [mtc_node_panda-1] [INFO] [1717010044.180531143] [mtc_node]: Try loading adapter 'default_planning_response_adapters/ValidateSolution' [mtc_node_panda-1] [INFO] [1717010044.183789536] [mtc_node]: Loaded adapter 'default_planning_response_adapters/ValidateSolution' [mtc_node_panda-1] [INFO] [1717010044.183900349] [mtc_node]: Try loading adapter 'default_planning_response_adapters/DisplayMotionPath' [mtc_node_panda-1] [INFO] [1717010044.186282417] [mtc_node]: Loaded adapter 'default_planning_response_adapters/DisplayMotionPath' [mtc_node_panda-1] [WARN] [1717010060.369908182] [planning_scene_interface_108803162633264.moveit.cartesian_interpolator]: The computed path is too short to detect jumps in joint-space. Need at least 10 steps, only got 6. Try a lower max_step. [mtc_node_panda-1] 0 - ← 0 → - 0 / demo task [mtc_node_panda-1] 1 - ← 1 → - 0 / current [mtc_node_panda-1] - 0 → 1 → - 1 / open hand [mtc_node_panda-1] - 1 → 0 ← 39 - / move to pick [mtc_node_panda-1] 39 - ← 39 → - 39 / pick object [mtc_node_panda-1] 40 - ← 40 ← 4 - / approach object [mtc_node_panda-1] 4 - ← 51 → - 4 / grasp pose IK [mtc_node_panda-1] 25 - ← 25 → - 25 / generate grasp pose [mtc_node_panda-1] - 4 → 47 → - 0 / allow collision (hand,object) [mtc_node_panda-1] - 0 → 47 → - 0 / close hand [mtc_node_panda-1] - 0 → 47 → - 0 / attach object [mtc_node_panda-1] - 0 → 47 → - 0 / allow collision (object,support) [mtc_node_panda-1] - 0 → 42 → - 0 / lift object [mtc_node_panda-1] - 0 → 42 → - 42 / forbid collision (object,surface) [mtc_node_panda-1] - 39 → 0 ← 0 - / move to place [mtc_node_panda-1] 0 - ← 0 → - 0 / place object [mtc_node_panda-1] 0 - ← 0 ← 0 - / lower object [mtc_node_panda-1] 0 - ← 0 → - 0 / place pose IK [mtc_node_panda-1] 390 - ← 390 → -390 / generate place pose [mtc_node_panda-1] - 0 → 0 → - 0 / open hand [mtc_node_panda-1] - 0 → 0 → - 0 / forbid collision (hand,object) [mtc_node_panda-1] - 0 → 0 → - 0 / detach object [mtc_node_panda-1] - 0 → 0 → - 0 / retreat [mtc_node_panda-1] - 0 → 0 → - 0 / return home [mtc_node_panda-1] Failing stage(s): [mtc_node_panda-1] place pose IK (0/390) [mtc_node_panda-1] [ERROR] [1717010060.919964371] [mtc_tutorial]: Task planning failed