Wall detection
をテンプレートにして作成
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開始行:
[[Autonomous Vehicles and Mobile Land/Aerial Robots/Drone...
*Abstract [#d90504bd]
- Proceed to vacant space by referring to the value of th...
- Judgment of the direction of travel is judged by using ...
- The learning test data of the neural network is generat...
1) Learning model
2) Learning Test Data Generator
- Swivelable distance
- Swivel condition branch
Code file: &ref(ai.py,,);,&ref(train_model.py,,);,&ref(la...
* Learning model [#jef5412e]
- Neural networks are created with multilayer perceptrons.
-- an input layer: 3, an output layer: 4, and an intermed...
-- Input: Each sensor value [left, front, right]
-- Output: The type of each action [STOP, LEFT, FRONT, RI...
CENTER:&ref(LM.png,,50%);
- Learning is done with supervised learning using test da...
-Implementation by TensorFlow.
-Hidden Neuron number changed result:&ref(result_hidden.p...
* Learning Test Data Generator [#t8eadb80]
-Generate pairs of values of three distance sensors and c...
--Input: Number of data to generate.
--Output: Each sensor value [left, front, right] and labe...
**Swivelable distance [#x77b2cd2]
-Based on the vehicle data, turn determination and stop d...
LEFT:&ref(VP.png,,35%);&ref(TD.png,,40%);
-#605 Motor Shield
-#902 Kerberos
-#105 Button
--Vehicle data
---Overall width:16.5cm
---Wheel base:19.0cm
---Nose:14.0cm
---Minimum turning radius:75cm
--Maximum turning radius:R
---R^2 = X^2 +Y^2 = 91.5^2 + 33^2, R = 97.27cm
--Turn determination distance: y_turn
---y_turn = R + margin_t = 100cm
--Inevitable distance: y_stop
--- r^2 = R^2 - (75 + 16.5/2)^2 = 97.27^2 - 83.25^2, r =...
--- y_stop = r - 33 + margin_s = 50.3 - 33 + margin_s = ...
**Swivel condition branch [#f7a0046f]
-Each of the three distance sensor values can be thought ...
--Pattern 0: Since the distance to the obstacle is far, n...
-> sensor > y_turn
--Pattern 1: Since the distance to the obstacle is short,...
-> sensor < y_turn
--Pattern 2: Since the distance to the obstacle is too cl...
-> sensor < y_stop
-Determine which of these patterns the left, front, right...
Next, create a branch to determine the direction of travel.
>>Control [sensor][pattern]:action
>>Control 1 [Front][2] :Stop because you can not go strai...
Control branch 1 [Left][0, 1]&[Front][1]&[Right] [0, 1] ...
--Control 2: When the distance is farther on the right. t...
--Control 3: When the distance is farther on the left. Tu...
>>Control 4 [Right][ 0 ]&[Front][ 0 ]&[Left][ 0 ]: Go str...
>>Control 5 [Left][1, 2]&[right][ 0 ]: The distance to th...
>>Control 6 [Left][ 0 ]&[Right][ 1, 2 ]:Right turn to the...
>>Control 7 [Left][ 2 ]&[Right][ 2 ]:Neither left nor rig...
Control branch 2 [Left][ 1 ]&[Right][ 1 ] : Both left an...
--Control 8: When the distance is farther on the right si...
--Control 9: When the distance is farther on the left. Tu...
>>Control 10 [Left][ 2 ]&[Right][ 1 ]: Left turn to the r...
>>Control 11 [Left][ 1 ]&[Right][ 2 ]: Right turn to the ...
*DEMO [#be34b673]
**Identical procedure [#y2c806c3]
-Login Raspberry PI (RobotCar)
>>ssh pi@192.168.xxx.xxx (192.168.11.31 10/15)
-Login docker conteiner
>>sudo su
>>docker exec -it CONTAINER_ID /bin/bash
-Move RobotCar directory
>>cd /notebooks/github/RobotCarAI/
**Progression direction prediction [#k38618ae]
# Current directory is /notebooks/github/RobotCarAI/
>>cd level1_sensors
>>python run_ai.py
-Directory (/notebooks/github/RobotCarAI/level1_sensors)
--document : document related
--fabolib : Fabo board related
--generator : Label generation related to learning data
--lib : forecast related
--MLP : Learning and pb file creation related
--model : learned model storage area
-Files (/notebooks/github/RobotCarAI/level1_sensors)
--run_ai_eval.py: Prediction accuracy evaluation code wit...
--run_ai_eval_400.py: Prediction accuracy evaluation code...
--run_ai.py: Code to retrieve sensor values and execute p...
--MLP/train_model.py: Learning execution code
---A log file for Tensorboard is output to MLP/log/
---A checkpoint file is output to MLP/model/
--MLP/freeze_graph.py: pb file creation code
---Create MLP/model/car_model.pb file
--MLP/run_ai_test.py: Code to execute prediction with ran...
**Driving Demo [#bc599a20]
# Current directory is /notebooks/github/RobotCarAI/
>>cd level1_demo/
>>python start_button.py
# To start running, press the blue button of the robot car
# To stop driving, press the red button on the robot car
-Directory
--document: Document related
--fabolib: Fabo board related
-- lib: SPI, AI library
-Files
--run_ai_ai.py: Automatic driving code
-- start_button.py: start button code
終了行:
[[Autonomous Vehicles and Mobile Land/Aerial Robots/Drone...
*Abstract [#d90504bd]
- Proceed to vacant space by referring to the value of th...
- Judgment of the direction of travel is judged by using ...
- The learning test data of the neural network is generat...
1) Learning model
2) Learning Test Data Generator
- Swivelable distance
- Swivel condition branch
Code file: &ref(ai.py,,);,&ref(train_model.py,,);,&ref(la...
* Learning model [#jef5412e]
- Neural networks are created with multilayer perceptrons.
-- an input layer: 3, an output layer: 4, and an intermed...
-- Input: Each sensor value [left, front, right]
-- Output: The type of each action [STOP, LEFT, FRONT, RI...
CENTER:&ref(LM.png,,50%);
- Learning is done with supervised learning using test da...
-Implementation by TensorFlow.
-Hidden Neuron number changed result:&ref(result_hidden.p...
* Learning Test Data Generator [#t8eadb80]
-Generate pairs of values of three distance sensors and c...
--Input: Number of data to generate.
--Output: Each sensor value [left, front, right] and labe...
**Swivelable distance [#x77b2cd2]
-Based on the vehicle data, turn determination and stop d...
LEFT:&ref(VP.png,,35%);&ref(TD.png,,40%);
-#605 Motor Shield
-#902 Kerberos
-#105 Button
--Vehicle data
---Overall width:16.5cm
---Wheel base:19.0cm
---Nose:14.0cm
---Minimum turning radius:75cm
--Maximum turning radius:R
---R^2 = X^2 +Y^2 = 91.5^2 + 33^2, R = 97.27cm
--Turn determination distance: y_turn
---y_turn = R + margin_t = 100cm
--Inevitable distance: y_stop
--- r^2 = R^2 - (75 + 16.5/2)^2 = 97.27^2 - 83.25^2, r =...
--- y_stop = r - 33 + margin_s = 50.3 - 33 + margin_s = ...
**Swivel condition branch [#f7a0046f]
-Each of the three distance sensor values can be thought ...
--Pattern 0: Since the distance to the obstacle is far, n...
-> sensor > y_turn
--Pattern 1: Since the distance to the obstacle is short,...
-> sensor < y_turn
--Pattern 2: Since the distance to the obstacle is too cl...
-> sensor < y_stop
-Determine which of these patterns the left, front, right...
Next, create a branch to determine the direction of travel.
>>Control [sensor][pattern]:action
>>Control 1 [Front][2] :Stop because you can not go strai...
Control branch 1 [Left][0, 1]&[Front][1]&[Right] [0, 1] ...
--Control 2: When the distance is farther on the right. t...
--Control 3: When the distance is farther on the left. Tu...
>>Control 4 [Right][ 0 ]&[Front][ 0 ]&[Left][ 0 ]: Go str...
>>Control 5 [Left][1, 2]&[right][ 0 ]: The distance to th...
>>Control 6 [Left][ 0 ]&[Right][ 1, 2 ]:Right turn to the...
>>Control 7 [Left][ 2 ]&[Right][ 2 ]:Neither left nor rig...
Control branch 2 [Left][ 1 ]&[Right][ 1 ] : Both left an...
--Control 8: When the distance is farther on the right si...
--Control 9: When the distance is farther on the left. Tu...
>>Control 10 [Left][ 2 ]&[Right][ 1 ]: Left turn to the r...
>>Control 11 [Left][ 1 ]&[Right][ 2 ]: Right turn to the ...
*DEMO [#be34b673]
**Identical procedure [#y2c806c3]
-Login Raspberry PI (RobotCar)
>>ssh pi@192.168.xxx.xxx (192.168.11.31 10/15)
-Login docker conteiner
>>sudo su
>>docker exec -it CONTAINER_ID /bin/bash
-Move RobotCar directory
>>cd /notebooks/github/RobotCarAI/
**Progression direction prediction [#k38618ae]
# Current directory is /notebooks/github/RobotCarAI/
>>cd level1_sensors
>>python run_ai.py
-Directory (/notebooks/github/RobotCarAI/level1_sensors)
--document : document related
--fabolib : Fabo board related
--generator : Label generation related to learning data
--lib : forecast related
--MLP : Learning and pb file creation related
--model : learned model storage area
-Files (/notebooks/github/RobotCarAI/level1_sensors)
--run_ai_eval.py: Prediction accuracy evaluation code wit...
--run_ai_eval_400.py: Prediction accuracy evaluation code...
--run_ai.py: Code to retrieve sensor values and execute p...
--MLP/train_model.py: Learning execution code
---A log file for Tensorboard is output to MLP/log/
---A checkpoint file is output to MLP/model/
--MLP/freeze_graph.py: pb file creation code
---Create MLP/model/car_model.pb file
--MLP/run_ai_test.py: Code to execute prediction with ran...
**Driving Demo [#bc599a20]
# Current directory is /notebooks/github/RobotCarAI/
>>cd level1_demo/
>>python start_button.py
# To start running, press the blue button of the robot car
# To stop driving, press the red button on the robot car
-Directory
--document: Document related
--fabolib: Fabo board related
-- lib: SPI, AI library
-Files
--run_ai_ai.py: Automatic driving code
-- start_button.py: start button code
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