void displayPlannerData(const planning_scene::PlanningSceneConstPtr& planning_scene,
const std::string &link_name) const
{
std::cout << "displayPlannerData called ... " << std::endl;
const ompl_interface::ModelBasedPlanningContextPtr &pc = ompl_interface_->getLastPlanningContext();
if (pc)
{
ompl::base::PlannerData pd(pc->getOMPLSimpleSetup().getSpaceInformation());
pc->getOMPLSimpleSetup().getPlannerData(pd);
robot_state::RobotState kstate = planning_scene->getCurrentState();
visualization_msgs::MarkerArray arr;
std_msgs::ColorRGBA color;
color.r = 1.0f;
color.g = 0.25f;
color.b = 1.0f;
color.a = 1.0f;
unsigned int nv = pd.numVertices();
for (unsigned int i = 0 ; i < nv ; ++i)
{
pc->getOMPLStateSpace()->copyToRobotState(kstate, pd.getVertex(i).getState());
kstate.getJointStateGroup(pc->getJointModelGroupName())->updateLinkTransforms();
const Eigen::Vector3d &pos = kstate.getLinkState(link_name)->getGlobalLinkTransform().translation();
visualization_msgs::Marker mk;
mk.header.stamp = ros::Time::now();
mk.header.frame_id = planning_scene->getPlanningFrame();
mk.ns = "planner_data";
mk.id = i;
mk.type = visualization_msgs::Marker::SPHERE;
mk.action = visualization_msgs::Marker::ADD;
mk.pose.position.x = pos.x();
mk.pose.position.y = pos.y();
mk.pose.position.z = pos.z();
mk.pose.orientation.w = 1.0;
mk.scale.x = mk.scale.y = mk.scale.z = 0.025;
mk.color = color;
mk.lifetime = ros::Duration(30.0);
arr.markers.push_back(mk);
}
pub_markers_.publish(arr);
}
}
bool ConvexConstraintSolver::solve(const planning_scene::PlanningSceneConstPtr& planning_scene,
const moveit_msgs::GetMotionPlan::Request &req,
moveit_msgs::GetMotionPlan::Response &res) const
{
// Need to add in joint limit constraints
// Get the position constraints from the collision detector
// The raw algorithm laid out in Chan et. al. is as follows:
// 1. Compute unconstrained motion to go from proxy to goal.
// 2. Get the current contact set by moving the proxy toward the goal by some epsilon and get all collision points.
// 3. Compute constrained motion (convex solver).
// 4. Compute collisions along the constrained motion path.
// 5. Set proxy to stop at the first new contact along path.
// In our framework this will look more like this:
// Outside ths planner:
// 1. Compute error between cartesian end effector and cartesian goal.
// 2. Cap pose error (based on some heuristic?) because we are about to make a linear approximation.
// 3. Use Jinverse to compute the joint deltas for the pose error (or perhaps we should frame this as a velocity problem).
// 4. Add the joint deltas to the start state to get a goal state.
// Inside the planner:
// 1. Get the "current" contact set by moving the proxy toward the goal by some epsilon and get all collision points.
// 2. Compute constrained motion (convex solver).
// 3. Subdivide motion subject to some sort of minimum feature size.
// 4. Move proxy in steps, checking for colliding state along the way. Optionally use interval bisection to refine.
// - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -/
std::string group_name = req.motion_plan_request.group_name;
std::string ee_group_name;
std::string ee_control_frame;
if(group_name == "right_arm"){ ee_group_name = "r_end_effector"; ee_control_frame = "r_wrist_roll_link"; }
if(group_name == "left_arm") { ee_group_name = "l_end_effector"; ee_control_frame = "l_wrist_roll_link"; }
ROS_WARN("Solving for group [%s], end-effector [%s], control frame [%s] using ConvexConstraintSolver!", group_name.c_str(), ee_group_name.c_str(), ee_control_frame.c_str());
// We "getCurrentState" just to populate the structure with auxiliary info, then copy in the transform info from the planning request.
planning_models::KinematicState start_state = planning_scene->getCurrentState();
planning_models::robotStateToKinematicState(*(planning_scene->getTransforms()), req.motion_plan_request.start_state, start_state);
// constrained_goal_state is the optimization output before interval stepping, proxy_state will be used as we step around.
planning_models::KinematicState proxy_state = start_state;
planning_models::KinematicState constrained_goal_state = start_state;
std::string planning_frame = ros::names::resolve("/", planning_scene->getPlanningFrame());
const planning_models::KinematicState::JointStateGroup * jsg = proxy_state.getJointStateGroup(group_name);
const planning_models::KinematicModel::JointModelGroup * jmg = planning_scene->getKinematicModel()->getJointModelGroup(group_name);
// std::string end_effector_group_name = jmg->getAttachedEndEffectorGroupName();
// const std::vector<std::string>& subgroups = jmg->getSubgroupNames();
// ROS_INFO("End-effector group name is [%s].", end_effector_group_name.c_str());
// for(size_t i = 0; i< subgroups.size(); i++)
// ROS_INFO("Subgroup [%zd] is [%s].", i, subgroups[i].c_str());
const planning_models::KinematicModel::JointModelGroup * ee_jmg = planning_scene->getKinematicModel()->getJointModelGroup(ee_group_name);
// const std::vector<const planning_models::KinematicModel::JointModel*>& joint_models = jmg->getJointModels();
// std::map<std::string, unsigned int> joint_index_map;
// for(size_t i = 0; i < joint_models.size(); i++)
// {
// //ROS_INFO("Group [%s] has joint %d: [%s]", req.motion_plan_request.group_name.c_str(), i, joint_models[i]->getName().c_str());
// joint_index_map[joint_models[i]->getName()] = i;
// }
const std::map<std::string, unsigned int>& joint_index_map = jmg->getJointVariablesIndexMap();
std::vector<double> limits_min, limits_max, joint_vector;
std::vector<std::string> joint_names;
limits_min.resize(7);
limits_max.resize(7);
joint_vector.resize(7);
joint_names.resize(7);
{
const moveit_msgs::Constraints &c = req.motion_plan_request.goal_constraints[1];
for (std::size_t i = 0 ; i < c.joint_constraints.size() ; ++i)
{
std::string joint_name = c.joint_constraints[i].joint_name;
if(joint_index_map.find(joint_name) == joint_index_map.end())
{
ROS_WARN("Didin't find [%s] in the joint map, ignoring...", joint_name.c_str());
continue;
}
unsigned int joint_index = joint_index_map.find(joint_name)->second;
std::vector<moveit_msgs::JointLimits> limits = planning_scene->getKinematicModel()->getJointModel(joint_name)->getLimits();
moveit_msgs::JointLimits limit = limits[0];
if(limit.has_position_limits)
{
limits_min[joint_index] = limit.min_position;
limits_max[joint_index] = limit.max_position;
}
else
{
limits_min[joint_index] = -1E3;
limits_max[joint_index] = 1E3;
}
joint_vector[joint_index] = start_state.getJointState(joint_name)->getVariableValues()[0];
joint_names[joint_index] = joint_name;
//ROS_INFO("Joint [%d] [%s] has min %.2f, value %.2f, max %.2f", joint_index, joint_name.c_str(), limits_min[joint_index], joint_vector[joint_index], limits_max[joint_index]);
}
}
// ======== Extract all contact points and normals from previous collision state, get associated Jacobians ========
std::vector<Eigen::MatrixXd> contact_jacobians;
std::vector<Eigen::Vector3d> contact_normals;
for( collision_detection::CollisionResult::ContactMap::const_iterator it = last_collision_result.contacts.begin(); it != last_collision_result.contacts.end(); ++it)
{
std::string contact1 = it->first.first;
std::string contact2 = it->first.second;
const std::vector<collision_detection::Contact>& vec = it->second;
for(size_t contact_index = 0; contact_index < vec.size(); contact_index++)
{
Eigen::Vector3d point = vec[contact_index].pos;
Eigen::Vector3d normal = vec[contact_index].normal;
double depth = vec[contact_index].depth;
ROS_INFO("Contact between [%s] and [%s] point: %.2f %.2f %.2f normal: %.2f %.2f %.2f depth: %.3f",
contact1.c_str(), contact2.c_str(),
point(0), point(1), point(2),
normal(0), normal(1), normal(2),
depth);
// Contact point needs to be expressed with respect to the link; normals should stay in the common frame
std::string group_contact;
if( jmg->hasLinkModel(contact1) || ee_jmg->hasLinkModel(contact1) ) group_contact = contact1;
else if( jmg->hasLinkModel(contact2) || ee_jmg->hasLinkModel(contact2) ) group_contact = contact2;
else
{
ROS_WARN("Contact isn't on group [%s], skipping...", req.motion_plan_request.group_name.c_str());
continue;
}
planning_models::KinematicState::LinkState *link_state = start_state.getLinkState(group_contact);
Eigen::Affine3d link_T_world = link_state->getGlobalCollisionBodyTransform().inverse();
point = link_T_world*point;
Eigen::MatrixXd jacobian;
if(jsg->getJacobian(group_contact, point, jacobian))
{
contact_jacobians.push_back(jacobian);
contact_normals.push_back(normal);
}
}
}
// ======== Extract goal "constraints" ========
const moveit_msgs::Constraints &c = req.motion_plan_request.goal_constraints[0];
// Position and Orientation
if(c.position_constraints.size() != 1 || c.orientation_constraints.size() != 1)
{
ROS_ERROR("Currently require exactly one position and orientation constraint. Aborting...");
return false;
}
moveit_msgs::PositionConstraint pc = c.position_constraints[0];
moveit_msgs::OrientationConstraint oc = c.orientation_constraints[0];
pc.header.frame_id = ros::names::resolve("/", pc.header.frame_id);
oc.header.frame_id = ros::names::resolve("/", oc.header.frame_id);
if(pc.link_name != oc.link_name)
{
ROS_ERROR("Currently can't support position and orientation goals that are not for the same link. Aborting...");
return false;
}
if(pc.constraint_region.primitive_poses.size() == 0)
{
ROS_ERROR("Need to specify a single primitive_pose for position constraint region. Aborting...");
return false;
}
if(pc.constraint_region.primitive_poses.size() != 1)
{
ROS_ERROR("Need exactly one 'pose' for the end-effector goal region. Aborting...");
}
if(pc.header.frame_id != planning_frame)
ROS_WARN("The position goal header [%s] and planning_frame [%s] don't match, things are probably all wrong!",
pc.header.frame_id.c_str(), planning_frame.c_str() );
if(oc.header.frame_id != planning_frame)
ROS_WARN("The orientation goal header [%s] and planning_frame [%s] don't match, things are probably all wrong!",
oc.header.frame_id.c_str(), planning_frame.c_str() );
Eigen::Vector3d goal_point;
Eigen::Quaterniond goal_quaternion_e;
{ // scoped so we don't pollute function scope with these message temps
geometry_msgs::Point msg_goal_point = pc.constraint_region.primitive_poses[0].position;
geometry_msgs::Quaternion msg_goal_orientation = oc.orientation;
goal_point = Eigen::Vector3d(msg_goal_point.x, msg_goal_point.y, msg_goal_point.z);
goal_quaternion_e = Eigen::Quaterniond(msg_goal_orientation.w, msg_goal_orientation.x, msg_goal_orientation.y, msg_goal_orientation.z);
}
//ROS_INFO("Computing position and orientation error...");
planning_models::KinematicState::LinkState *link_state = start_state.getLinkState(pc.link_name);
Eigen::Affine3d planning_T_link = link_state->getGlobalLinkTransform();
Eigen::Vector3d ee_point_in_ee_frame = Eigen::Vector3d(pc.target_point_offset.x, pc.target_point_offset.y, pc.target_point_offset.z);
Eigen::Vector3d ee_point_in_planning_frame = planning_T_link*ee_point_in_ee_frame;
// TODO need to make sure these are expressed in the same frame.
Eigen::Vector3d x_error = goal_point - ee_point_in_planning_frame;
Eigen::Vector3d delta_x = x_error;
double x_error_mag = x_error.norm();
double LINEAR_CLIP = 0.02;
if(x_error_mag > LINEAR_CLIP)
delta_x = x_error/x_error_mag*LINEAR_CLIP;
// = = = = Rotations are gross = = = =
Eigen::Quaterniond link_quaternion_e = Eigen::Quaterniond(planning_T_link.rotation());
tf::Quaternion link_quaternion_tf, goal_quaternion_tf;
tf::RotationEigenToTF( link_quaternion_e, link_quaternion_tf );
tf::RotationEigenToTF( goal_quaternion_e, goal_quaternion_tf );
tf::Quaternion delta_quaternion = link_quaternion_tf.inverse()*goal_quaternion_tf;
double rotation_angle = delta_quaternion.getAngle();
//tf::Vector3 rotation_axis = delta_quaternion.getAxis();
//ROS_INFO("Delta is [%.3f] radians about [%.3f, %.3f, %.3f]", rotation_angle, rotation_axis.x(), rotation_axis.y(), rotation_axis.z());
double ANGLE_CLIP = 0.2;
double clipped_rotation_fraction = std::min<double>(1.0, ANGLE_CLIP/fabs(rotation_angle));
if(clipped_rotation_fraction < 0) ROS_ERROR("Clipped rotation fraction < 0, look into this!");
tf::Matrix3x3 clipped_delta_matrix;
tf::Quaternion clipped_goal_quaternion = link_quaternion_tf.slerp(goal_quaternion_tf, clipped_rotation_fraction);
clipped_delta_matrix.setRotation( link_quaternion_tf.inverse()*clipped_goal_quaternion );
tf::Vector3 delta_euler;
clipped_delta_matrix.getRPY(delta_euler[0], delta_euler[1], delta_euler[2]);
//ROS_INFO("Delta euler in link frame = [%.3f, %.3f, %.3f]", delta_euler[0], delta_euler[1], delta_euler[2]);
tf::Matrix3x3 link_matrix(link_quaternion_tf);
delta_euler = link_matrix * delta_euler;
//ROS_INFO("Delta euler in planning_frame = [%.3f, %.3f, %.3f]", delta_euler[0], delta_euler[1], delta_euler[2]);
// Get end-effector Jacobian
// std::string ee_control_frame = "r_wrist_roll_link";
// if(false && jmg->isChain())
// ee_control_frame = planning_scene->getKinematicModel()->getJointModelGroup(jmg->getAttachedEndEffectorGroupName())->getEndEffectorParentGroup().second;
// else
// ROS_WARN("Using r_wrist_roll_link as HARD_CODED value.");
if(ee_control_frame != pc.link_name)
ROS_WARN("ee_control_frame [%s] and position_goal link [%s] aren't the same, this could be bad!", ee_control_frame.c_str(), pc.link_name.c_str());
// ROS_INFO("Getting end-effector Jacobian for local point %.3f, %.3f, %.3f on link [%s]",
// ee_point_in_ee_frame(0),
// ee_point_in_ee_frame(1),
// ee_point_in_ee_frame(2),
// ee_control_frame.c_str());
Eigen::MatrixXd ee_jacobian;
if(!jsg->getJacobian(ee_control_frame , ee_point_in_ee_frame , ee_jacobian))
{
ROS_ERROR("Unable to get end-effector Jacobian! Can't plan, exiting...");
return false;
}
//ROS_INFO_STREAM("End-effector jacobian in planning frame is: \n" << ee_jacobian);
// ======== Pack into solver data structure, run solver. ========
//ROS_INFO("Packing data into the cvx solver...");
// Vars vars;
// Params params;
// Workspace work;
// Settings settings;
// CVX Settings
cvx.set_defaults();
cvx.setup_indexing();
cvx.settings.verbose = 0;
// - - - - - - - load all problem instance data - - - - - - - //
unsigned int N = 7; // number of joints in the chain
// end-effector Jacobian
// TODO magic numbers (though I suppose the CVX solver is already hard-coded)
for(unsigned int row = 0; row < 3; row++ )
{
for(unsigned int col = 0; col < N; col++ )
{
// CVX matrices are COLUMN-MAJOR!!!
cvx.params.J_v[col*3 + row] = ee_jacobian(row, col);
cvx.params.J_w[col*3 + row] = ee_jacobian(row+3, col);
}
}
// Set weights for objective terms
cvx.params.weight_x[0] = 1.0; // translational error
cvx.params.weight_w[0] = 0.1; // angular error (error in radians is numerically much larger than error in meters)
cvx.params.weight_q[0] = 0.001; // only want to barely encourage values to stay small...
// set up constraints from contact set
unsigned int MAX_CONSTRAINTS = 25;
unsigned int constraint_count = std::min<size_t>(MAX_CONSTRAINTS, contact_normals.size());
for(unsigned int constraint = 0; constraint < MAX_CONSTRAINTS; constraint++)
{
if(constraint < constraint_count)
{
// CVX matrices are COLUMN-MAJOR!!!
for (int j = 0; j < 3*7; j++) {
cvx.params.J_c[constraint][j] = contact_jacobians[constraint](j%3, j/3);
}
for (int j = 0; j < 3; j++) {
cvx.params.normal[constraint][j] = contact_normals[constraint][j];
}
}
else{
//printf("setting to zero\n");
for (int j = 0; j < 3*7; j++) {
cvx.params.J_c[constraint][j] = 0;
}
for (int j = 0; j < 3; j++) {
cvx.params.normal[constraint][j] = 0;
}
}
}
for(unsigned int index = 0; index < N; index++ )
{
cvx.params.q[index] = joint_vector[index];
cvx.params.q_min[index] = limits_min[index];
cvx.params.q_max[index] = limits_max[index];
}
// TODO should these be clipped down at all? :)
for(unsigned int index = 0; index < 3; index++ )
{
cvx.params.x_d[index] = delta_x(index); // TODO magic minus sign!!
cvx.params.w_d[index] = delta_euler[index];
}
// - - - - - - - Solve our problem at high speed! - - - - - - - //
long num_iters = 0;
num_iters = cvx.solve();
if(!cvx.work.converged)
{
printf("solving failed to converge in %ld iterations.\n", num_iters);
return false;
}
// ======== Unpack solver result into constrained goal state. ========
ROS_INFO("Finished solving in %ld iterations, unpacking data...", num_iters);
Eigen::VectorXd joint_deltas(N);
std::map<std::string, double> goal_update;
for(size_t joint_index = 0; joint_index < joint_names.size(); joint_index++)
{
std::string joint_name = joint_names[joint_index];
joint_deltas(joint_index) = cvx.vars.q_d[joint_index];
goal_update[joint_name] = cvx.vars.q_d[joint_index] + start_state.getJointState(joint_name)->getVariableValues()[0];
//ROS_INFO("Updated joint [%zd] [%s]: %.3f + %.3f", joint_index, joint_name.c_str(), start_state.getJointState(joint_name)->getVariableValues()[0], cvx.vars.q_d[joint_index]);
}
Eigen::VectorXd cartesian_deltas = ee_jacobian*joint_deltas;
//ROS_INFO("Raw Error: translate [%.3f, %.3f, %.3f]",
// x_error(0), x_error(1), x_error(2));
ROS_INFO("ClipError: translate [%.3f, %.3f, %.3f] euler [%.2f, %.2f, %.2f]",
delta_x(0), delta_x(1), delta_x(2),
delta_euler[0], delta_euler[1], delta_euler[2]);
ROS_INFO("Output: translate [%.3f, %.3f, %.3f] euler [%.2f, %.2f, %.2f]",
cartesian_deltas(0), cartesian_deltas(1), cartesian_deltas(2),
cartesian_deltas(3), cartesian_deltas(4), cartesian_deltas(5));
//goal_update[vars.qdd_c[index] + ]
constrained_goal_state.setStateValues(goal_update);
// ======== Step toward constrained goal, checking for new collisions along the way ========
//double proxy_goal_tolerance = 0.1;
double interpolation_progress = 0.0;
double interpolation_step = 0.34;
collision_detection::CollisionResult collision_result;
while(interpolation_progress <= 1.0)
{
//ROS_INFO("Doing interpolation, with progress %.2f ", interpolation_progress);
// TODO this interpolation scheme might not allow the arm to slide along contacts very well...
planning_models::KinematicStatePtr point;
point.reset(new planning_models::KinematicState(constrained_goal_state));
start_state.interpolate(constrained_goal_state, interpolation_progress, *point);
// get contact set
collision_detection::CollisionRequest collision_request;
// TODO magic number
collision_request.max_contacts = 50;
collision_request.contacts = true;
collision_request.distance = false;
collision_request.verbose = false;
collision_result.clear();
planning_scene->checkCollision(collision_request, collision_result, *point);
if(collision_result.collision)
{
break;
}
else
{
proxy_state = *point;
}
// TODO Use proxy_goal_tolerance to exit if we are close enough!
interpolation_progress += interpolation_step;
}
// Store the last collision result!
last_collision_result = collision_result;
// ======== Convert proxy state to a "trajectory" ========
//ROS_INFO("Converting proxy to a trajectory, and returning...");
moveit_msgs::RobotTrajectory rt;
trajectory_msgs::JointTrajectory traj;
trajectory_msgs::JointTrajectoryPoint pt;
sensor_msgs::JointState js;
planning_models::kinematicStateToJointState(proxy_state, js);
//const planning_models::KinematicModel::JointModelGroup *jmg = planning_scene->getKinematicModel()->getJointModelGroup(req.motion_plan_request.group_name);
// getJointNames
for(size_t i = 0 ; i < js.name.size(); i++)
{
std::string name = js.name[i];
if( !jmg->hasJointModel(name) ) continue;
traj.joint_names.push_back(js.name[i]);
pt.positions.push_back(js.position[i]);
if(js.velocity.size()) pt.velocities.push_back(js.velocity[i]);
}
pt.time_from_start = ros::Duration(req.motion_plan_request.allowed_planning_time*1.0);
traj.points.push_back(pt);
traj.header.stamp = ros::Time::now();
traj.header.frame_id = "odom_combined";
res.trajectory.joint_trajectory = traj;
return true;
}