fix

src/Algorithms/Libraries/mkt_algorithm/src/diff/diff_predictive_trajectory.cpp

@@ -636,26 +636,28 @@ void mkt_algorithm::diff::PredictiveTrajectory::computePurePursuit(
   double w_target = v_target * kappa;
   if(journey(trajectory.poses, 0, trajectory.poses.size() - 1) <= min_journey_squared_)
   {
-    ss << w_target << " ";
     if (trajectory.poses.size() >= 2) {
       const auto& p1 = trajectory.poses[trajectory.poses.size() - 1].pose;
       double heading_ref = 0.0;
       for(int i = trajectory.poses.size() - 2; i >= 0; i--)
       {
         const auto& p = trajectory.poses[i].pose;
-        const auto& dx = sign_x < 0.0 ? p1.x - p.x : p.x - p1.x;
+        const auto& dx =  p1.x - p.x ;
-        const auto& dy = sign_x < 0.0 ? p1.y - p.y : p.y - p1.y;
+        const auto& dy =  p1.y - p.y ;
         if(std::hypot(dx, dy) >= costmap_robot_->getCostmap()->getResolution())
         {
           if(fabs(dx) < 1e-6 && fabs(dy) < 1e-6)
             continue;
-          heading_ref = angles::normalize_angle(std::atan2(dy, dx));
+          heading_ref = std::atan2(dy, dx);
+          ss << "error " << heading_ref << " ";
+          if(sign_x < 0.0)
+          heading_ref += std::copysign(M_PI, heading_ref) * (-1.0);
           break;
         }
       }
 
-      const double error = angles::normalize_angle(heading_ref);
+      const double error = heading_ref;
-      ss << "error: " << error << " ";
+      ss << error << " ";
       double w_heading = 0.0;
       pid(error, 
         near_goal_heading_integral_, 
@@ -667,12 +669,12 @@ void mkt_algorithm::diff::PredictiveTrajectory::computePurePursuit(
         w_heading);
       // Apply acceleration limits
       double dw_heading = std::clamp(w_heading - velocity.theta, -acc_lim_theta_ * dt, acc_lim_theta_ * dt);
+      ss << "dw_heading " << dw_heading << " ";
       w_target = velocity.theta + dw_heading;
-      ss << w_target << " ";
     }
     else
     {
-      w_target = 0.0;
+      w_target = std::clamp(w_target, -0.001, 0.001);
       near_goal_heading_was_active_ = false;
     }
   }
@@ -690,7 +692,6 @@ void mkt_algorithm::diff::PredictiveTrajectory::computePurePursuit(
   drive_cmd.x = velocity.x + dv;
   drive_cmd.theta = velocity.theta + dw;
 
-  ss  << drive_cmd.theta << " ";
   Eigen::VectorXd y(2);
   y << drive_cmd.x, drive_cmd.theta;
 
@@ -710,7 +711,7 @@ void mkt_algorithm::diff::PredictiveTrajectory::computePurePursuit(
   drive_cmd.x = fabs(drive_cmd.x) >= v_min ? drive_cmd.x : std::copysign(v_min, sign_x);
   if (kf_filter_angular_)
     drive_cmd.theta = std::clamp(kf_->state()[3], -max_vel_theta_, max_vel_theta_);
-  ROS_WARN_THROTTLE(0.1, "%s", ss.str().c_str());
+  // robot::log_info("%s", ss.str().c_str());
 }
 
 void mkt_algorithm::diff::PredictiveTrajectory::applyDistanceSpeedScaling(
@@ -774,16 +775,22 @@ bool mkt_algorithm::diff::PredictiveTrajectory::shouldRotateToPath(
     for(int i = 2; i < global_plan.poses.size(); i++)
     {
       const auto& p = global_plan.poses[i];
+      const auto& dx = p.pose.x - p1.pose.x;
+      const auto& dy = p.pose.y - p1.pose.y;
       if(std::hypot(p.pose.x, p.pose.y) > costmap_robot_->getCostmap()->getResolution())
       {
-        path_angle = std::atan2(p.pose.y - p1.pose.y, p.pose.x - p1.pose.x);
+        if(fabs(dx) < 1e-9 && fabs(dy) < 1e-9)
+          continue;
+        path_angle = std::atan2(dy, dx);
         break;
       }
     }
   }
   
   // Whether we should rotate robot to rough path heading
-  angle_to_path = sign_x < 0.0 ? angles::normalize_angle(M_PI + path_angle) : path_angle;
+  if(sign_x < 0.0)
+    path_angle += std::copysign(M_PI, path_angle) * (-1.0);
+  angle_to_path = path_angle;
   double heading_linear = sqrt(velocity.x * velocity.x + velocity.y * velocity.y);
   // The difference in the path orientation and the starting robot orientation (radians) to trigger a rotate in place. (default: 0.785)
   double heading_rotate = rotate_to_heading_min_angle_;
@@ -1241,7 +1248,7 @@ robot_nav_2d_msgs::Path2D mkt_algorithm::diff::PredictiveTrajectory::generateTra
 
   if (max_kappa <= straight_threshold && fabs(path.poses.back().pose.x) < min_lookahead_dist_) // nếu đường thẳng
   { 
-    if(fabs(path.poses.front().pose.y) <= 0.03 && fabs(path.poses.back().pose.x) < (min_lookahead_dist_ + max_path_distance_))
+    if(fabs(path.poses.front().pose.y) <= 0.03 && fabs(path.poses.back().pose.x) < min_lookahead_dist_ )
     {
       return generateParallelPath(path, sign_x);
     }