From a1f783b8e0acd381e0f6226af0baf5c5d313db99 Mon Sep 17 00:00:00 2001 From: Yoshihiro Kogure Date: Thu, 19 Dec 2024 12:05:11 +0900 Subject: [PATCH 1/6] Improve README Signed-off-by: Yoshihiro Kogure --- control_data_collecting_tool/README.md | 92 ++++++++++++++++++ .../resource/boundary.png | Bin 0 -> 23723 bytes .../resource/boundary_counter_clockwise.png | Bin 0 -> 26226 bytes .../resource/circumcircle.png | Bin 0 -> 40613 bytes .../circumcircle_counter_clockwise.png | Bin 0 -> 42882 bytes .../resource/common_tangent.png | Bin 0 -> 47572 bytes .../common_tangent_counter_clockwise.png | Bin 0 -> 49721 bytes .../resource/looking_ahead.png | Bin 0 -> 17543 bytes .../resource/whole_trajectory.png | Bin 0 -> 38923 bytes 9 files changed, 92 insertions(+) create mode 100644 control_data_collecting_tool/resource/boundary.png create mode 100644 control_data_collecting_tool/resource/boundary_counter_clockwise.png create mode 100644 control_data_collecting_tool/resource/circumcircle.png create mode 100644 control_data_collecting_tool/resource/circumcircle_counter_clockwise.png create mode 100644 control_data_collecting_tool/resource/common_tangent.png create mode 100644 control_data_collecting_tool/resource/common_tangent_counter_clockwise.png create mode 100644 control_data_collecting_tool/resource/looking_ahead.png create mode 100644 control_data_collecting_tool/resource/whole_trajectory.png diff --git a/control_data_collecting_tool/README.md b/control_data_collecting_tool/README.md index 6a51a257..78aa1158 100644 --- a/control_data_collecting_tool/README.md +++ b/control_data_collecting_tool/README.md @@ -181,6 +181,98 @@ You can create an original mask to specify the data collection range for the hea +## Trajectory generation and data collection logic + +- ### Data collection logic common to all courses + + In `control_data_collection_tool`, all courses collect velocity and acceleration data in a similar manner. + + By appropriately adjusting the `target_velocity` provided to the pure pursuit algorithm, speed and acceleration data are efficiently collected. Data collection consists of four phases: selection of target speed and acceleration, acceleration phase, constant speed phase, the deceleration phase. A general method for collecting speed and acceleration data is described below, though it does not strictly adhere to the outlined steps. + + 1. Selection of target speed and acceleration + + In the speed-acceleration heatmap, the speed and acceleration with fewer data points are set as the target speed and acceleration, which are then defined here as `target_velocity_on_section` and `target_acceleration_on_section`. + + 2. Acceleration phase + The vehicle accelerates by setting `target_velocity` as follows until its speed exceeds `target_velocity_on_section`. + + ```Python3 + # sine_curve is derived from appropriate amplitude and period, defined separately + target_velocity = current_velocity + abs(target_acceleration_on_section) / acc_kp + sine_curve + ``` + + `current_velocity` is a current velocity of vehicle and `acc_kp` accel command proportional gain in pure pursuit algorithm. `sine_curve` is a sine wave added to partially mitigate situations where the vehicle fails to achieve the target acceleration. + + 3. Constant speed phase + When the vehicle reaches `target_velocity_on_section`, `target_velocity` is defined as follows to allow the vehicle to run around the target speed for a certain period of time. + + ```Python3 + # sine_curve is derived from appropriate amplitude and period, defined separately + target_velocity = target_velocity_on_section + sine_curve + sine_curve + ``` + + 4. Deceleration phase + In the deceleration phase, similar to the acceleration phase, `target_velocity` is defined as follows to ensure the vehicle decelerates. + + ```Python3 + # sine_curve is derived from appropriate amplitude and period, defined separately + target_velocity = current_velocity - abs(target_acceleration_on_section) / acc_kp + sine_curve + ``` + + After decelerating to a sufficiently low speed, return to step i. + +- ### Trajectory generation and data collection logic specific to `reversal_loop_circle` + + In the `reversal_loop_circle` course, sections are sequentially added to the course while collecting various data on speed, acceleration, and steering angle. + +- #### Trajectory generation logic for `reversal_loop_circle` + + The `reversal_loop_circle` aims to generate a trajectory with the largest possible radius of curvature within a radius `trajectory_radius`, allowing data collection in a confined area without significantly reducing speed. + + The `reversal_loop_circle` is primarily generated by connecting the following three components, `common tangent`, `circumcircle` and `boundary` as shown in the following picture. + + + + All the components listed below are available in both clockwise and counterclockwise versions. The rationale for having two versions is to ensure data collection for both right-hand drive and left-hand drive configurations. + + - `common tangent` + + The `common tangent` is generated by drawing a common tangent to two inscribed circles. In this section, a sine curve is added in the normal direction to generate a trajectory for collecting data with larger steering angles. + The amplitude of the sine curve is determined based on the desired steering angle data. + + + + + + - `circumcircle` + + The `circumcircle` part is created by drawing the common circumscribed circle of the circles. + This section is generated to achieve nearly straight movement within the outer circle while minimizing the increase in curvature. + + + + + + - `boundary` + + The `boundary` part is used to connect the `common tangent` and the `circumcircle` sections. + + + + + +- #### Velocity and steering angle data collection logic for `reversal_loop_circle` + + Speed and steering angle data are gathered in the `common tangent` section of the trajectory. The common tangent section is particularly effective for collecting steering angle data because a trajectory with minimal data is intentionally created by adding a sine wave of suitable amplitude to the curvature. + + The following two steps are taken to obtain steering angle data. + + 1. Starting from the ego vehicle's current position, the system examines a segment of the trajectory ahead, covering a distance defined by looking_ahead_distance, to identify the point of maximum curvature. + + 2. This maximum curvature determines the steering angle the vehicle will use. The vehicle then adjusts its speed toward the speed associated with the sparsest steering angle data. + + + ## Parameter There are parameters that are common to all trajectories and parameters that are specific to each trajectory. diff --git a/control_data_collecting_tool/resource/boundary.png b/control_data_collecting_tool/resource/boundary.png new file mode 100644 index 0000000000000000000000000000000000000000..8cc3b88ea9d6a5280afaca7c5b216077449ee9ca GIT binary patch literal 23723 zcmdqJhdb8q|2}@JG*FU6Wz=0F$v26E=i_{w=M|uRle4Y8 zow(2eAyL5{Hdn4VI3E-izWo3Ff{?wFwQ!U9L?J$8orBsbX9|Vcocv4oNHN2fLNVr0 zS3YFmmN@*&)y?2U*QfE()S0Ba8#Qe7=nn;!-1w>zzhlL#8!0Kzf}UI+&S&74JV|f7 zaUX5{J}QG+#GV~0N_Vv%UB7j=jV~^4etwsj;>t&ncV#OJlKU#NYicYfv|Y}(B|4AF zY$+9CQpP`Jm)&Byl*oS)h-OHk;h%)#bemaNSRBO#e5v@y?kK%3`MuglltBD6cPpC` ze##>Ca0Nep+GS-xQNfQ}ga4oVV=XE3532;XFxuMMTB+vQoPBrYzGjS&RryAiJpTXR z(v+!i_#HAgzuzpXT(+L9QMI)9g7nSR>#4hU-}?Mn_h>N3`+>%cd!e$N8}{fVX+1o8 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zK5gu&gifGoc$Q^W2N^m2b?!x)rjmYeL~DU`&@s(`u9D?zi}@r(a+~@;FCs!LbL3Sg z4Q}HUjO5MqPj@tY{Ql9gWa+MbadM8U>UZDq#|o|(e+RaB8h}?Qx!md ztcbaD>H{N|^%Zx~vCP$IaC(IfNX)!^eJMr;#qU+wQk3p*>x!J=e3w|F;i6pUX4bvY&NIczg4?{P&bC(uVFcnX^AAF`su8cN3l_ z(Pnw7NAr|Rl9STR$eAf$Pb--kO`XyqVzkKkMBhm@Q>9SrBv+Sxs=XUJza+)YpAIY; zzpks2y4$;@Z0n;JB@bSde5rZ&rs&bPU4^^vY}vm3abEf3tn!ODFLJUOv`KdQbRWqu zOFGc7{cQKeY?V7weRq?N=WP|16!dJ-ZR*&-@n}uqk(-Y?wjL8o?|xl5C&m9z(x#fy z3_-!4$3kuZ7eKo>%@OPC0D>0a$O7=F!HELEoDDq0Pv{X$nrk*t)}tdhQ5Y!ASqMy` oK%nT?>I>AYas*fj43Or({4?FUO`EF=mM{Q;r>mdKI;Vst09%v&s{jB1 literal 0 HcmV?d00001 From 1590388ed2e2d22ffaae849bcfa105e3bbf6d0ee Mon Sep 17 00:00:00 2001 From: Yoshihiro Kogure Date: Thu, 19 Dec 2024 12:12:31 +0900 Subject: [PATCH 2/6] Modify data collction logic Signed-off-by: Yoshihiro Kogure --- control_data_collecting_tool/README.md | 4 +- .../config/common_param.yaml | 2 +- .../reversal_loop_circle_param.yaml | 2 +- .../scripts/courses/reversal_loop_circle.py | 57 +++++++++---------- .../data_collecting_trajectory_publisher.py | 2 +- 5 files changed, 32 insertions(+), 35 deletions(-) diff --git a/control_data_collecting_tool/README.md b/control_data_collecting_tool/README.md index 78aa1158..66b53e3d 100644 --- a/control_data_collecting_tool/README.md +++ b/control_data_collecting_tool/README.md @@ -296,7 +296,7 @@ ROS 2 parameters which are common in all trajectories (`/config/common_param.yam | `STEER_MAX` | `double` | Maximum steer in heatmap [rad] | 0.6 | | `A_MIN` | `double` | Minimum acceleration in heatmap [m/s^2] | -1.0 | | `A_MAX` | `double` | Maximum acceleration in heatmap [m/s^2] | 1.0 | -| `max_lateral_accel` | `double` | Max lateral acceleration limit [m/s^2] | 2.00 | +| `max_lateral_accel` | `double` | Max lateral acceleration limit [m/s^2] | 2.70 | | `ABS_STEER_RATE_MIN` | `double` | Minimum absolute value of steer rate in heatmap [rad/s] | 0.0 | | `ABS_STEER_RATE_MAX` | `double` | Maximum absolute value of steer rate in heatmap [rad/s] | 0.3 | | `JERK_MIN` | `double` | Minimum jerk in heatmap [m/s^3] | -0.5 | @@ -371,7 +371,7 @@ Each trajectory has specific ROS 2 parameters. | :-------------------- | :------- | :---------------------------------------------------------------------------------- | :------------ | | `trajectory_radius` | `double` | Radius of the circle where trajectories are generated [m] | 35.0 | | `enclosing_radius` | `double` | Radius of the circle enclosing the generated trajectories [m] | 40.0 | -| `look_ahead_distance` | `double` | The distance referenced ahead of the vehicle for collecting steering angle data [m] | 15.0 | +| `look_ahead_distance` | `double` | The distance referenced ahead of the vehicle for collecting steering angle data [m] | 35.0 | - `COURSE_NAME: along_road` diff --git a/control_data_collecting_tool/config/common_param.yaml b/control_data_collecting_tool/config/common_param.yaml index 1a578f0b..3e5c12c4 100644 --- a/control_data_collecting_tool/config/common_param.yaml +++ b/control_data_collecting_tool/config/common_param.yaml @@ -30,7 +30,7 @@ VEL_STEER_THRESHOLD: 20 VEL_ABS_STEER_RATE_THRESHOLD: 20 - max_lateral_accel: 2.00 + max_lateral_accel: 2.70 lateral_error_threshold: 1.50 yaw_error_threshold: 0.75 velocity_limit_by_tracking_error: 1.0 diff --git a/control_data_collecting_tool/config/course_param/reversal_loop_circle_param.yaml b/control_data_collecting_tool/config/course_param/reversal_loop_circle_param.yaml index 09621529..55939b39 100644 --- a/control_data_collecting_tool/config/course_param/reversal_loop_circle_param.yaml +++ b/control_data_collecting_tool/config/course_param/reversal_loop_circle_param.yaml @@ -3,7 +3,7 @@ # Course Specific Parameters trajectory_radius: 35.0 enclosing_radius: 40.0 - look_ahead_distance: 15.0 + look_ahead_distance: 35.0 # Data Collection Range COLLECTING_DATA_V_MIN: 0.5 diff --git a/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py b/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py index 2fb26d8e..4d8552e2 100644 --- a/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py +++ b/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py @@ -752,7 +752,7 @@ def declare_reversal_loop_circle_params(node): node.declare_parameter( "look_ahead_distance", - 15.0, + 35.0, ParameterDescriptor( description="The distance referenced ahead of the vehicle for collecting steering angle data" ), @@ -1030,74 +1030,74 @@ def get_target_velocity( self.vehicle_phase = "acceleration" self.updated_target_velocity = True + self.alpha = 0.5 + np.random.randint(0,2) * 0.5 + acc_kp_of_pure_pursuit = self.params.acc_kp # Proportional gain for acceleration control - T = 10.0 # Period of the sine wave used to modulate velocity + # Period should be parameterized + T = 5.0 # Period of the sine wave used to modulate velocity sine = np.sin(2 * np.pi * current_time / T) # Sine wave for smooth velocity modulation + target_acc = 0.0 # Handle acceleration phase if self.vehicle_phase == "acceleration": if current_vel < self.target_vel_on_segmentation - 1.0 * abs( self.target_acc_on_segmentation ): # Increase velocity with a maximum allowable acceleration - target_vel = current_vel + self.params.a_max / acc_kp_of_pure_pursuit * ( - 1.25 + 0.50 * sine - ) + target_acc = self.alpha * self.params.a_max / acc_kp_of_pure_pursuit * (0.4 + 0.6 * sine) else: # Increase velocity with a absolute target acceleration - target_vel = current_vel + abs( + target_acc = abs( self.target_acc_on_segmentation - ) / acc_kp_of_pure_pursuit * (1.25 + 0.50 * sine) + ) / acc_kp_of_pure_pursuit + 0.1 * sine # Transition to "constant speed" phase once the target velocity is reached if current_vel > self.target_vel_on_segmentation: self.vehicle_phase = "constant_speed" self.const_velocity_start_time = current_time - # Handle constant speed phase - if self.vehicle_phase == "constant_speed": - # Modulate velocity around the target with a sine wave - target_vel = self.target_vel_on_segmentation + 2.0 * (-0.5 + 1.0 * sine) - - # Transition to "deceleration" phase after a fixed duration - if current_time - self.const_velocity_start_time > T: - self.vehicle_phase = "deceleration" - # Handle deceleration phase if self.vehicle_phase == "deceleration": if current_vel < self.target_vel_on_segmentation - 1.0 * abs( self.target_acc_on_segmentation ): # Decrease velocity with a maximum deceleration - target_vel = current_vel - self.params.a_max / acc_kp_of_pure_pursuit * ( - 1.25 + 0.50 * sine - ) + target_acc = - self.alpha * self.params.a_max / acc_kp_of_pure_pursuit * (0.4 + 0.6 * sine) else: # Decrease velocity with a absolute target acceleration - target_vel = current_vel - abs( + target_acc = - abs( self.target_acc_on_segmentation - ) / acc_kp_of_pure_pursuit * (1.25 + 0.50 * sine) + ) / acc_kp_of_pure_pursuit + 0.1 * sine # Reset velocity update flag when deceleration is complete if ( current_vel - < self.target_vel_on_segmentation - - 1.0 * abs(self.target_acc_on_segmentation) / acc_kp_of_pure_pursuit + < self.target_vel_on_segmentation / 4.0 ): self.updated_target_velocity = False # Maintain a smoothed velocity by averaging recent values + # 10.0 should be parameterized + target_vel = current_vel + target_acc + 10.0 * (target_acc - current_acc) + + # Handle constant speed phase + if self.vehicle_phase == "constant_speed": + # Modulate velocity around the target with a sine wave + target_vel = self.target_vel_on_segmentation + 2.0 * np.sin(2 * np.pi * current_time / 5.0) * np.sin(2 * np.pi * current_time / 10.0) - 2.0 + if current_time - self.const_velocity_start_time > 20.0: + self.vehicle_phase = "deceleration" + self.vel_hist.append(target_vel) target_vel = np.mean(self.vel_hist) # Special handling for trajectory direction changes if self.trajectory_list[2].in_direction is not self.trajectory_list[2].out_direction: # Set a fixed target velocity during direction transitions - target_vel = 3.0 + 1.0 * sine + target_vel = 2.0 + 2.0 * sine # Adjust velocity based on trajectory curvature and lateral acceleration constraints - if (self.trajectory_list[1].in_direction is not self.trajectory_list[1].out_direction) or ( - self.trajectory_list[2].in_direction is not self.trajectory_list[2].out_direction + if (self.trajectory_list[0].in_direction is not self.trajectory_list[0].out_direction) or ( + self.trajectory_list[1].in_direction is not self.trajectory_list[1].out_direction ): max_curvature_on_segment = 1e-9 # Initialize to a small value to avoid division by zero max_lateral_vel_on_segment = 1e9 # Initialize to a large value as a placeholder @@ -1140,10 +1140,7 @@ def get_target_velocity( max_vel_from_lateral_acc_on_segment = np.sqrt( self.params.max_lateral_accel / max_curvature_on_segment ) - target_vel = np.min([target_vel_ + 0.5 * sine, max_vel_from_lateral_acc_on_segment]) - - # Ensure the target velocity remains above a minimum threshold - target_vel = np.max([target_vel, 0.5]) + target_vel = np.min([target_vel_ + 1.0 * sine**2, max_vel_from_lateral_acc_on_segment]) return target_vel diff --git a/control_data_collecting_tool/scripts/data_collecting_trajectory_publisher.py b/control_data_collecting_tool/scripts/data_collecting_trajectory_publisher.py index e7f91c32..c3c2d41b 100755 --- a/control_data_collecting_tool/scripts/data_collecting_trajectory_publisher.py +++ b/control_data_collecting_tool/scripts/data_collecting_trajectory_publisher.py @@ -72,7 +72,7 @@ def __init__(self): self.declare_parameter( "lateral_error_threshold", - 2.0, + 2.70, ParameterDescriptor( description="Lateral error threshold where applying velocity limit [m/s]" ), From 59497b7a0e513cd6f7173a6d8334b25bf5665fbb Mon Sep 17 00:00:00 2001 From: Yoshihiro Kogure Date: Thu, 19 Dec 2024 12:21:58 +0900 Subject: [PATCH 3/6] Final adjustment Signed-off-by: Yoshihiro Kogure --- control_data_collecting_tool/README.md | 20 +++++----- .../scripts/courses/reversal_loop_circle.py | 39 ++++++++++++------- 2 files changed, 34 insertions(+), 25 deletions(-) diff --git a/control_data_collecting_tool/README.md b/control_data_collecting_tool/README.md index 66b53e3d..18b92c9e 100644 --- a/control_data_collecting_tool/README.md +++ b/control_data_collecting_tool/README.md @@ -231,7 +231,7 @@ You can create an original mask to specify the data collection range for the hea The `reversal_loop_circle` is primarily generated by connecting the following three components, `common tangent`, `circumcircle` and `boundary` as shown in the following picture. - + All the components listed below are available in both clockwise and counterclockwise versions. The rationale for having two versions is to ensure data collection for both right-hand drive and left-hand drive configurations. @@ -240,26 +240,26 @@ You can create an original mask to specify the data collection range for the hea The `common tangent` is generated by drawing a common tangent to two inscribed circles. In this section, a sine curve is added in the normal direction to generate a trajectory for collecting data with larger steering angles. The amplitude of the sine curve is determined based on the desired steering angle data. - + - + - `circumcircle` The `circumcircle` part is created by drawing the common circumscribed circle of the circles. This section is generated to achieve nearly straight movement within the outer circle while minimizing the increase in curvature. - + - + - `boundary` The `boundary` part is used to connect the `common tangent` and the `circumcircle` sections. - + - + - #### Velocity and steering angle data collection logic for `reversal_loop_circle` @@ -267,11 +267,11 @@ You can create an original mask to specify the data collection range for the hea The following two steps are taken to obtain steering angle data. - 1. Starting from the ego vehicle's current position, the system examines a segment of the trajectory ahead, covering a distance defined by looking_ahead_distance, to identify the point of maximum curvature. + 1. Starting from the ego vehicle's current position, the system examines a segment of the trajectory ahead, covering a distance defined by looking_ahead_distance, to identify the point of maximum curvature. - 2. This maximum curvature determines the steering angle the vehicle will use. The vehicle then adjusts its speed toward the speed associated with the sparsest steering angle data. + 2. This maximum curvature determines the steering angle the vehicle will use. The vehicle then adjusts its speed toward the speed associated with the sparsest steering angle data. - + ## Parameter diff --git a/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py b/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py index 4d8552e2..441d2caf 100644 --- a/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py +++ b/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py @@ -1030,7 +1030,7 @@ def get_target_velocity( self.vehicle_phase = "acceleration" self.updated_target_velocity = True - self.alpha = 0.5 + np.random.randint(0,2) * 0.5 + self.alpha = 0.5 + np.random.randint(0, 2) * 0.5 acc_kp_of_pure_pursuit = self.params.acc_kp # Proportional gain for acceleration control # Period should be parameterized @@ -1044,12 +1044,14 @@ def get_target_velocity( self.target_acc_on_segmentation ): # Increase velocity with a maximum allowable acceleration - target_acc = self.alpha * self.params.a_max / acc_kp_of_pure_pursuit * (0.4 + 0.6 * sine) + target_acc = ( + self.alpha * self.params.a_max / acc_kp_of_pure_pursuit * (0.4 + 0.6 * sine) + ) else: # Increase velocity with a absolute target acceleration - target_acc = abs( - self.target_acc_on_segmentation - ) / acc_kp_of_pure_pursuit + 0.1 * sine + target_acc = ( + abs(self.target_acc_on_segmentation) / acc_kp_of_pure_pursuit + 0.1 * sine + ) # Transition to "constant speed" phase once the target velocity is reached if current_vel > self.target_vel_on_segmentation: @@ -1062,18 +1064,17 @@ def get_target_velocity( self.target_acc_on_segmentation ): # Decrease velocity with a maximum deceleration - target_acc = - self.alpha * self.params.a_max / acc_kp_of_pure_pursuit * (0.4 + 0.6 * sine) + target_acc = ( + -self.alpha * self.params.a_max / acc_kp_of_pure_pursuit * (0.4 + 0.6 * sine) + ) else: # Decrease velocity with a absolute target acceleration - target_acc = - abs( - self.target_acc_on_segmentation - ) / acc_kp_of_pure_pursuit + 0.1 * sine + target_acc = ( + -abs(self.target_acc_on_segmentation) / acc_kp_of_pure_pursuit + 0.1 * sine + ) # Reset velocity update flag when deceleration is complete - if ( - current_vel - < self.target_vel_on_segmentation / 4.0 - ): + if current_vel < self.target_vel_on_segmentation / 4.0: self.updated_target_velocity = False # Maintain a smoothed velocity by averaging recent values @@ -1083,7 +1084,13 @@ def get_target_velocity( # Handle constant speed phase if self.vehicle_phase == "constant_speed": # Modulate velocity around the target with a sine wave - target_vel = self.target_vel_on_segmentation + 2.0 * np.sin(2 * np.pi * current_time / 5.0) * np.sin(2 * np.pi * current_time / 10.0) - 2.0 + target_vel = ( + self.target_vel_on_segmentation + + 2.0 + * np.sin(2 * np.pi * current_time / 5.0) + * np.sin(2 * np.pi * current_time / 10.0) + - 2.0 + ) if current_time - self.const_velocity_start_time > 20.0: self.vehicle_phase = "deceleration" @@ -1140,7 +1147,9 @@ def get_target_velocity( max_vel_from_lateral_acc_on_segment = np.sqrt( self.params.max_lateral_accel / max_curvature_on_segment ) - target_vel = np.min([target_vel_ + 1.0 * sine**2, max_vel_from_lateral_acc_on_segment]) + target_vel = np.min( + [target_vel_ + 1.0 * sine**2, max_vel_from_lateral_acc_on_segment] + ) return target_vel From f00a65b5eddf8e473592c0ba2d36a4c39194e59c Mon Sep 17 00:00:00 2001 From: Yoshihiro Kogure Date: Thu, 19 Dec 2024 13:07:38 +0900 Subject: [PATCH 4/6] Spelling correction Signed-off-by: Yoshihiro Kogure --- control_data_collecting_tool/README.md | 12 ++++++------ .../resource/circumcircle.png | Bin 40613 -> 0 bytes .../circumcircle_counter_clockwise.png | Bin 42882 -> 0 bytes .../resource/circumscribing_circle.png | Bin 0 -> 41673 bytes ...ircumscribing_circle_counter_clockwise.png | Bin 0 -> 43624 bytes .../resource/whole_trajectory.png | Bin 38923 -> 39916 bytes 6 files changed, 6 insertions(+), 6 deletions(-) delete mode 100644 control_data_collecting_tool/resource/circumcircle.png delete mode 100644 control_data_collecting_tool/resource/circumcircle_counter_clockwise.png create mode 100644 control_data_collecting_tool/resource/circumscribing_circle.png create mode 100644 control_data_collecting_tool/resource/circumscribing_circle_counter_clockwise.png diff --git a/control_data_collecting_tool/README.md b/control_data_collecting_tool/README.md index 18b92c9e..a041f438 100644 --- a/control_data_collecting_tool/README.md +++ b/control_data_collecting_tool/README.md @@ -229,7 +229,7 @@ You can create an original mask to specify the data collection range for the hea The `reversal_loop_circle` aims to generate a trajectory with the largest possible radius of curvature within a radius `trajectory_radius`, allowing data collection in a confined area without significantly reducing speed. - The `reversal_loop_circle` is primarily generated by connecting the following three components, `common tangent`, `circumcircle` and `boundary` as shown in the following picture. + The `reversal_loop_circle` is primarily generated by connecting the following three components, `common tangent`, `circumscribing_circle` and `boundary` as shown in the following picture. @@ -244,18 +244,18 @@ You can create an original mask to specify the data collection range for the hea - - `circumcircle` + - `circumscribing_circle` - The `circumcircle` part is created by drawing the common circumscribed circle of the circles. + The `circumscribing_circle` part is created by drawing the common circumscribed circle of the circles. This section is generated to achieve nearly straight movement within the outer circle while minimizing the increase in curvature. - + - + - `boundary` - The `boundary` part is used to connect the `common tangent` and the `circumcircle` sections. + The `boundary` part is used to connect the `common tangent` and the `circumscribing_circle` sections. diff --git a/control_data_collecting_tool/resource/circumcircle.png b/control_data_collecting_tool/resource/circumcircle.png deleted file mode 100644 index 6b9016eb61fb60e5b903999bf8cc21fb94a1b31c..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 40613 zcmeEuhdb79`1V6KNw%yskgYPavPyP52$^N?z4x9;p^z2w$liN}B3aohJ3D*xUeEV; zyzlY8|HIpH`0~ZW=f3ajzOM5+&+`(lqV(h{!3_cg0&!LDsq}LM0@DwH!1#lQ1E1mR zpIm@% zZZU?^44B-fg~Pp^&JEO z`lAJEe82y`C?t!S4qsrBj)_CCqQ521`2T+k?9l(aFW23KBPo*&}g zq$YA`yDGqAKPSyWNhl*Dvku?jb++A!`1-PrQbyHny`;0YJj+pY{p@&Gl|0zC@i@eN zcPTC{P1(?pDN)}?DDG(x1-ph_-(%caCt(^-;%y{omlM1fRa=D 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zzpks2y4$;@Z0n;JB@bSde5rZ&rs&bPU4^^vY}vm3abEf3tn!ODFLJUOv`KdQbRWqu zOFGc7{cQKeY?V7weRq?N=WP|16!dJ-ZR*&-@n}uqk(-Y?wjL8o?|xl5C&m9z(x#fy z3_-!4$3kuZ7eKo>%@OPC0D>0a$O7=F!HELEoDDq0Pv{X$nrk*t)}tdhQ5Y!ASqMy` oK%nT?>I>AYas*fj43Or({4?FUO`EF=mM{Q;r>mdKI;Vst09%v&s{jB1 From 3e7b3fc735c9ba6143567a02f4b99b3acb40a44b Mon Sep 17 00:00:00 2001 From: Yoshihiro Kogure Date: Thu, 19 Dec 2024 13:08:48 +0900 Subject: [PATCH 5/6] pre-commit run Signed-off-by: Yoshihiro Kogure --- control_data_collecting_tool/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/control_data_collecting_tool/README.md b/control_data_collecting_tool/README.md index a041f438..e262adf9 100644 --- a/control_data_collecting_tool/README.md +++ b/control_data_collecting_tool/README.md @@ -267,9 +267,9 @@ You can create an original mask to specify the data collection range for the hea The following two steps are taken to obtain steering angle data. - 1. Starting from the ego vehicle's current position, the system examines a segment of the trajectory ahead, covering a distance defined by looking_ahead_distance, to identify the point of maximum curvature. + 1. Starting from the ego vehicle's current position, the system examines a segment of the trajectory ahead, covering a distance defined by looking_ahead_distance, to identify the point of maximum curvature. - 2. This maximum curvature determines the steering angle the vehicle will use. The vehicle then adjusts its speed toward the speed associated with the sparsest steering angle data. + 2. This maximum curvature determines the steering angle the vehicle will use. The vehicle then adjusts its speed toward the speed associated with the sparsest steering angle data. From ebaf27e1f6dccdae89525b2060c16190665cd34b Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Thu, 19 Dec 2024 04:32:22 +0000 Subject: [PATCH 6/6] style(pre-commit): autofix --- .../scripts/courses/reversal_loop_circle.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py b/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py index 13774ef0..108df22d 100644 --- a/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py +++ b/control_data_collecting_tool/scripts/courses/reversal_loop_circle.py @@ -1147,9 +1147,7 @@ def get_target_velocity( max_vel_from_lateral_acc_on_segment = np.sqrt( self.params.max_lateral_accel / max_curvature_on_segment ) - target_vel = np.min( - [target_vel_ + 1.0 * sine**2, max_vel_from_lateral_acc_on_segment] - ) + target_vel = np.min([target_vel_ + 1.0 * sine**2, max_vel_from_lateral_acc_on_segment]) return target_vel