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steap_test_benedikt.m
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close all
clear
import gtsam.*
import gpmp2.*
%%ROS Config
% rosshutdown
% rosinit
%
% server = rossvcserver('/steap_plan', 'carrot_planner/path_array', @serviceCallback,...
% 'DataFormat','struct');
% req = rosmessage(server);
% Arrays that saves current trajectory
%global x_array
%global y_array
%% generate map & sdf
dataset = generate2Ddataset('MobileMap1');
rows = dataset.rows;
cols = dataset.cols;
cell_size = dataset.cell_size;
origin = [0, 0, 0];
origin_point3 = Point3(origin');
% sdf
disp('calculating signed distance field ...');
field = signedDistanceField3D(dataset.map, dataset.cell_size);
disp('calculating signed distance field done');
% init sdf
sdf = SignedDistanceField(origin_point3, cell_size, size(field, 1), ...
size(field, 2), size(field, 3));
for z = 1:size(field, 3)
sdf.initFieldData(z-1, field(:,:,z)');
end
%% generate mobile arm model
% base_T_arm = Pose3(Rot3(eye(3)), Point3([0,0,0]'));
% arm: JACO2 6DOF arm
% alpha = [0]';
% a = [0]';
% d = [0]';
% % theta = [0, 0, 0, 0, 0, 0]';
% % abstract arm
% arm = Arm(0, a, alpha, d);
% % abstract mobile arm
% marm = Pose2MobileArm(arm, base_T_arm);
% % sphere data [id x y z r]
% spheres_data = [...
% 0 0.0 0.0 0.0 0.8
% ];
%
% nr_body = size(spheres_data, 1);
%
% sphere_vec = BodySphereVector;
% for i=1:nr_body
% sphere_vec.push_back(BodySphere(spheres_data(i,1), spheres_data(i,5), ...
% Point3(spheres_data(i,2:4)')));
% end
% arm_model = generateMobileArm('');
% arm model
arm_model = generateMobileArm('SimpleTwoLinksArm');
% GP
Qc = 1 * eye(5);
Qc_model = noiseModel.Gaussian.Covariance(Qc);
% Obstacle avoid settings
cost_sigma = 0.1;
epsilon_dist = 0.1;
% noise model
pose_fix_sigma = 0.0001;
vel_fix_sigma = 0.0001;
% prior to start/goal >> You cannnot fix start and goal position because
% its a SREAP problem and it involves change in pose i.e. replanning setup
%pose_fix = noiseModel.Isotropic.Sigma(5, 0.0001);
%vel_fix = noiseModel.Isotropic.Sigma(5, 0.0001);
%% settings
error_mode = 0;
total_time_sec = 2.0;
total_time_step = 10; %how many variable nodes
total_check_step = 10;
delta_t = total_time_sec / total_time_step;
check_inter = total_check_step / total_time_step - 1;
% check_inter = 5;
% delta_t = total_time_sec / total_time_step;
% total_check_step = (check_inter + 1)*total_time_step;
% use 2d vehicle dynamics
use_vehicle_dynamics = true;
dynamics_sigma = 0.001;
% start and end conf
start_pose = Pose2(-1, 0, pi/2);
start_conf = [0, 0]';
pstart = Pose2Vector(start_pose, start_conf);
start_vel = [0, 0, 0, 0, 0]';
end_pose = Pose2(1, 0, pi/2);
end_conf = [1, 1]';
pend = Pose2Vector(end_pose, end_conf);
end_vel = [0, 0, 0, 0, 0]';
avg_vel = [end_pose.x()-start_pose.x(); end_pose.y()-start_pose.y(); ...
end_pose.theta()-start_pose.theta(); (end_conf / total_time_step)] / delta_t;
% plot param
pause_time = total_time_sec / total_time_step;
%optimization settings
opt_setting = TrajOptimizerSetting(5);
opt_setting.set_total_step(total_time_step);
opt_setting.set_total_time(total_time_sec);
opt_setting.set_epsilon(epsilon_dist);
opt_setting.set_cost_sigma(cost_sigma);
opt_setting.set_obs_check_inter(check_inter);
opt_setting.set_conf_prior_model(pose_fix_sigma);
opt_setting.set_vel_prior_model(vel_fix_sigma);
opt_setting.set_Qc_model(Qc);
% opt_setting.set_total_step(total_time_step);
% opt_setting.set_total_time(total_time_sec);
% opt_setting.set_conf_prior_model(pose_fix_sigma);
% opt_setting.set_vel_prior_model(vel_fix_sigma);
%
% opt_setting.set_flag_pos_limit(flag_limit);
% opt_setting.set_flag_vel_limit(flag_limit);
% opt_setting.set_joint_pos_limits_up(joint_limit_vec_up);
% opt_setting.set_joint_pos_limits_down(joint_limit_vec_down);
% opt_setting.set_vel_limits(joint_vel_limit_vec);
% opt_setting.set_pos_limit_thresh(joint_limit_thresh);
% opt_setting.set_vel_limit_thresh(joint_vel_limit_thresh);
% opt_setting.set_pos_limit_model(joint_limit_model);
% opt_setting.set_vel_limit_model(joint_vel_limit_model);
%
% opt_setting.set_epsilon(epsilon_dist);
% opt_setting.set_cost_sigma(cost_sigma);
% opt_setting.set_obs_check_inter(check_inter);
%
% opt_setting.set_Qc_model(Qc);
%
% opt_setting.setDogleg();
%% initial values
% init_values = Values;
%
% for i = 0 : total_time_step
% key_pos = symbol('x', i);
% key_vel = symbol('v', i);
%
% % initialize as straight line in conf space
% conf = start_conf * (total_time_step-i)/total_time_step + end_conf * i/total_time_step;
% pose = Pose2(start_pose.x() * (total_time_step-i)/total_time_step + ...
% end_pose.x() * i/total_time_step, ...
% start_pose.y() * (total_time_step-i)/total_time_step + ...
% end_pose.y() * i/total_time_step, ...
% start_pose.theta() * (total_time_step-i)/total_time_step + ...
% end_pose.theta() * i/total_time_step);
% vel = avg_vel;
%
% insertPose2VectorInValues(key_pos, Pose2Vector(pose, conf), init_values);
% init_values.insert(key_vel, vel);
% end
%% initialize STEAP / ISAM
init_values = initPose2VectorTrajStraightLine(start_pose, start_conf, end_pose, end_conf, total_time_step);
% batch_values = BatchTrajOptimizePose2MobileArm(arm_model, sdf, pstart, start_vel, pend, end_vel, init_values, opt_setting);
%%
marm_inc_inf = ISAM2TrajOptimizerPose2MobileArm(arm_model, sdf, opt_setting);
marm_inc_inf.initFactorGraph(pstart, start_vel, pend, end_vel);
marm_inc_inf.initValues(batch_values);
marm_inc_inf.update();
inc_inf_values = marm_inc_inf.values();
%% STEAP
% figure(4)
% hold on
% plotEvidenceMap2D(dataset.map, dataset.origin_x, dataset.origin_y, cell_size);
%
% xlim([0 10])
% ylim([0 10])
%
% %plot initial trajectory
% plot_inter = check_inter;
% total_plot_step = total_time_step * (plot_inter + 1);
% plot_values = interpolatePose2Traj(inc_inf_values, Qc_model, delta_t, plot_inter, 0, total_time_step);
% plot_trajectory(plot_values, total_plot_step, 'r');
%
%% execute Trajectory
% for i = 0 : total_time_step - 1
% key_pos = symbol('x', i+1);
% goal = inc_inf_values.atPose2(key_pos);
%
% plot_inter = check_inter; %interpolate to next time step
% total_plot_step = total_time_step * (plot_inter + 1);
% exec_values = interpolatePose2Traj(inc_inf_values, Qc_model, delta_t, 5, i, i+1);
% plot_trajectory(exec_values, total_plot_step, 'b');
%
% coll_cost = CollisionCostPose2MobileBase2D(robot, sdf, exec_values, opt_setting); %calculate collision cost
%
% if coll_cost ~= 0 && error_mode == 1
% error("At step %i, plan is not collision free (Collision Cost: %i)", i, coll_cost);
% end
%
% %execute Trajectory --> Send it to ROS
% provide_trajectory(exec_values, 6);
% [x_ist, y_ist, t_ist] = send_goal(goal.x, goal.y, goal.theta);
%
% %get current state and use if it was measured recently then
% %update factor graph to perform incremental inference
% plot(x_ist, y_ist, 'O g');
%
% pose_estimate = Pose2(x_ist, y_ist, t_ist);
% estimation_noise = noiseModel.Diagonal.Sigmas([0.1; 0.1; 15]);
% marm_inc_inf.addPoseEstimate(i + 1, pose_estimate, estimation_noise);
% marm_inc_inf.update();
% inc_inf_values = marm_inc_inf.values();
% end
%
% %% FUNCTIONS
% %ROS Trajectory Service
% function provide_trajectory(Values, steps)
% global x_array;
% global y_array;
%
% [x_array, y_array] = values_to_array(Values, steps);
% end
%
% function resp = serviceCallback(~,req,resp)
% global x_array;
% global y_array;
% resp.PathXArray(1) = x_array(1);
%
% i = 1;
% while x_array(i) ~= 0 && y_array(i) ~= 0
% resp.PathXArray(i) = x_array(i);
% resp.PathYArray(i) = y_array(i);
% i = i + 1;
% end
% end
%
% %Other Functions
% function plot_trajectory(values, plot_step, color)
% import gtsam.*;
% import gpmp2.*;
% for i = 0 : plot_step
% if i>0
% try
% p0_x = values.atPose2(symbol('x', i)).x;
% p0_y = values.atPose2(symbol('x', i)).y;
%
% p1_x = values.atPose2(symbol('x', i-1)).x;
% p1_y = values.atPose2(symbol('x', i-1)).y;
%
% % plotPlanarMobileBase(robot.fk_model(), p, [0.4 0.2], 'b', 1);
% plot([p0_x p1_x], [p0_y p1_y], color);
% catch
% break;
% end
% end
% end
% end