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diff --git a/3D Design/battery case (origami)/battery_3.studio3 b/3D Design/battery case (origami)/battery_3.studio3
new file mode 100644
index 0000000000000000000000000000000000000000..03a884e5ec85225cf7b41bb3cefe31c722aad762
Binary files /dev/null and b/3D Design/battery case (origami)/battery_3.studio3 differ
diff --git a/Code/Control/Laptop_Code/ESP32_AT/imageTread_AT.py b/Code/Control/Laptop_Code/ESP32_AT/imageTread_AT.py
index 4fdade85df85c73c0641473b3dea9062fe91e1a8..f17cf50b98ea65da0647eafb4182d8a98671f471 100644
--- a/Code/Control/Laptop_Code/ESP32_AT/imageTread_AT.py
+++ b/Code/Control/Laptop_Code/ESP32_AT/imageTread_AT.py
@@ -36,7 +36,8 @@ def get_AT_6DOF_info(url):
fy = 600
cx = 400
cy = 300
- AT_size = 0.16
+ #AT_size = 0.16
+ AT_size = 0.74
results = detector.detect(gray_image, estimate_tag_pose=True, camera_params=[fx, fy, cx, cy], tag_size=AT_size)
debug_print = 0
for r in results:
@@ -97,6 +98,11 @@ if __name__ == "__main__":
# url='http://192.168.1.107/cam-hi.jpg'
url='http://192.168.4.1/cam-hi.jpg'
url = 'http://192.168.1.118/cam-hi.jpg'
+ url = 'http://10.0.0.3/cam-hi.jpg' #03
+ url = 'http://10.0.0.5/cam-hi.jpg' #01
+ url = 'http://10.0.0.6/cam-hi.jpg' #02
+ url = 'http://10.0.0.7/cam-hi.jpg' #06
+
# cv2.namedWindow("live transmission", cv2.WINDOW_AUTOSIZE)
diff --git a/Code/Control/Laptop_Code/ESP32_slave/ESP32_slave.ino b/Code/Control/Laptop_Code/ESP32_slave/ESP32_slave.ino
index c32e3b41b30ed8d5dc0e58491546bf190020a22c..f79c97c83061e6cf1f75ad7859c7af98c83b4f03 100644
--- a/Code/Control/Laptop_Code/ESP32_slave/ESP32_slave.ino
+++ b/Code/Control/Laptop_Code/ESP32_slave/ESP32_slave.ino
@@ -121,7 +121,7 @@ void OnDataRecv(const uint8_t * mac, const uint8_t *incomingData, int len) {
//Create the interface that will be used by the camera
openmv::rpc_scratch_buffer<256> scratch_buffer; // All RPC objects share this buffer.
openmv::rpc_i2c_master interface(0x12, 100000); //to make this more robust, consider making address and rate as constructor argument
-Camera cam(&interface);
+//Camera cam(&interface);
// ========================== Motor part ====================================
// Create the motor shield object with the default I2C address
Adafruit_MotorShield AFMS = Adafruit_MotorShield();
@@ -195,7 +195,7 @@ void loop()
int y = 0;
bool goalfind_flag = 0;
- goalfind_flag = cam.exe_goalfinder(goal_id[0],goal_id[1],goal_id[2], id, tx, ty, tz, rx, ry, rz);
+// goalfind_flag = cam.exe_goalfinder(goal_id[0],goal_id[1],goal_id[2], id, tx, ty, tz, rx, ry, rz);
if (goalfind_flag){
Sent_tx = tx;
Sent_ty = ty;
diff --git a/Code/Control/Laptop_Code/ball_detection/ball_detection.py b/Code/Control/Laptop_Code/ball_detection/ball_detection.py
index f35e2f847384cd7b5e0a62e0d75132a9a210d627..8e8f45f471757e00a417702f16a0127860554b28 100644
--- a/Code/Control/Laptop_Code/ball_detection/ball_detection.py
+++ b/Code/Control/Laptop_Code/ball_detection/ball_detection.py
@@ -23,9 +23,9 @@ distanceDetect = __import__('ball_detection.distance-detection-torch.distance-de
# change the IP address below according to the IP shown in the Serial monitor of Arduino code
# url='http://192.168.1.107/cam-lo.jpg'
-url='http://192.168.4.1/cam-hi.jpg'
+# url='http://192.168.4.1/cam-hi.jpg'
# url='http://192.168.1.107/cam-mid.jpg'
-url='http://192.168.0.204/cam-hi.jpg' # url2
+# url='http://192.168.0.204/cam-hi.jpg' # url2
#### Modify Detecto Core to include possibility of other base models
def modifyCore():
@@ -81,7 +81,7 @@ def returnModel(device, labelSet, modelLoc, modelFile):
return model
#### Live Detection
-def detectLive(model, minDetectionScore = 0.90, showSight = True):
+def detectLive(url , model, minDetectionScore = 0.90, showSight = True):
'''
Descrption:
ball detection ML Functions
diff --git a/Code/Control/Laptop_Code/ball_detection/ball_detection_full.py b/Code/Control/Laptop_Code/ball_detection/ball_detection_full.py
deleted file mode 100644
index ee9dceaa208cff7dc279518acd52ca0286831657..0000000000000000000000000000000000000000
--- a/Code/Control/Laptop_Code/ball_detection/ball_detection_full.py
+++ /dev/null
@@ -1,255 +0,0 @@
-## Codebase - Live Training-based Ball Detection
-### Import Modules and Drive
-import os
-import cv2
-import glob
-import torch
-import numpy as np
-import torch.nn as nn
-import torch.quantization
-import matplotlib.pyplot as plt
-import matplotlib.patches as patches
-
-from urllib.request import urlopen, Request #
-
-from base64 import b64decode
-from datetime import datetime
-from matplotlib import patches
-from detecto import core, utils
-from torchvision import transforms
-from matplotlib import pyplot as plt
-distanceDetect = __import__('ball_detection.distance-detection-torch.distance-detection-torch', fromlist = ['distanceDetect']).distanceDetect
-print("torch.cuda.is_available() = ", torch.cuda.is_available())
-
-minDetectionScore = 0.50
-
-# change the IP address below according to the IP shown in the Serial monitor of Arduino code
-# url='http://192.168.1.107/cam-lo.jpg'
-url='http://192.168.4.1/cam-hi.jpg'
-# url='http://192.168.1.107/cam-mid.jpg'
-
-#### Modify Detecto Core to include possibility of other base models
-def modifyCore():
- cModLineNums = [221, 253, 254]
- cAddLineNums = [254, 256, 257, 258, 259]
-
- # REPLACABLE LINE FOR DIFFERENT LOCAL COMPUTER DEVICES
- coreFile = 'C:\\Users\\uclal\\.conda\\envs\\foray2\\Lib\\site-packages\\detecto\\core.py'
-
- cModLineVals = [" def __init__(self, classes=None, device=None, pretrained=True, modelname=\'fasterrcnn_resnet50_fpn\'):\n",
- " # Load a model pre-trained on COCO - User-Modified",
- " self._model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=pretrained)\n"]
- cAddLineVals = [" if modelname == \'fasterrcnn_resnet50_fpn\':\n",
- " elif modelname == \'fasterrcnn_mobilenet_v3_large_fpn\':\n",
- " self._model = torchvision.models.detection.fasterrcnn_mobilenet_v3_large_fpn(pretrained=pretrained)\n",
- " elif modelname == \'fasterrcnn_mobilenet_v3_large_320_fpn\':\n",
- " self._model = torchvision.models.detection.fasterrcnn_mobilenet_v3_large_320_fpn(pretrained=pretrained)\n",
- " else:",
- " return ValueError('Unknown Pretrained Model')"]
- coreRead = open(coreFile, "r")
- coreLines = coreRead.readlines()
- if coreLines[253][-14:-1] != 'User-Modified':
- for count, cModLineNum in enumerate(cModLineNums):
- coreLines[cModLineNum] = cModLineVals[count]
- for count, cAddLineNum in enumerate(cAddLineNums):
- coreLines.insert(cAddLineNum, cAddLineVals[count])
- coreRead.close()
- coreWrite = open(coreFile, "w")
- coreWrite.writelines(coreLines)
- coreWrite.close()
-
-### Train the Model
-def modelName(type = 1):
- if type == 1:
- return 'fasterrcnn_resnet50_fpn'
- elif type == 2:
- return 'fasterrcnn_mobilenet_v3_large_fpn'
- elif type == 3:
- return 'fasterrcnn_mobilenet_v3_large_320_fpn'
- else:
- return ValueError('Unknown Pretrained Model')
-
-def modelTitle(modelLoc, device, type):
- time = datetime.now().strftime("%Y%m%d_%H%M%S")
- if device == 'cpu':
- dev = 'cpu'
- elif device[:4] == 'cuda':
- dev = 'cuda'
- print("using cuda")
- return modelLoc + 'model_weights-' + str(type) + '-' + time + '-' + dev + '.pth'
-
-def returnModel(modelAction, device, trainLoc, labelSet, modelLoc, modelFile):
- if modelAction == 'new':
- dataset = core.Dataset(trainLoc)
- model = core.Model(labelSet, device = device, modelname = modelName(modelType))
- losses = model.fit(dataset, epochs = 10, verbose = True)
- model.save(modelTitle(modelLoc, device, modelType))
- elif modelAction == 'load':
- model = core.Model(labelSet, modelname = modelname)
- #model = core.Model(classes = labelSet, device = device, pretrained = True, model_name = modelName(modelType))
- model._model.load_state_dict(torch.load(modelLoc + modelFile, map_location = torch.device(device)))
- # model = torch.quantization.quantize_dynamic(model.get_internal_model(), dtype=torch.qint8)
- return model
-
-### Object Detection
-def objectDetection(loc):
- image = utils.read_image(loc)
- predictions = model.predict(image)
- tLabels, tBoxes, tScores = predictions
- labels, boxes, scores = [[] for i in range(3)]
- imHeight, imWidth, _ = image.shape
- for count, box in enumerate(tBoxes):
- x0, y0 = float(box[0]), float(box[1])
- x1, y1 = float(box[2]), float(box[3])
- w = x1 - x0
- h = y1 - y0
- center = (x0 + (w/2), y0 + (h/2))
- dCrop = [int(y0*cropFactor + y1*(1-cropFactor)), int(y1*cropFactor + y0*(1-cropFactor)),
- int(x0*cropFactor + x1*(1-cropFactor)), int(x1*cropFactor + x0*(1-cropFactor))]
- distance = distanceDetect('load-testImg', distWtsFile, [[x0, x1, y0, y1], [imWidth, imHeight]])
- avgClRGB = cv2.mean(image[dCrop[0]:dCrop[1], dCrop[2]:dCrop[3]])
- avgClHue = rgbToHue(avgClRGB)
- print('Detection Score : ', round(float(tScores[count])*100, 2), '%')
- print('Average Color (RGB) : ', avgClRGB)
- print('Average Color (Hue) : ', avgClHue)
- print('Bounding Box Center : ', center)
- print('Distance to Ball : ', distance)
- # print('Relative Distance : ', relativeDist)
- # print('Coordinates : ', coordinates)
- print()
- if tScores[count] > minDetectionScore and avgClHue > colorLow and avgClHue < colorHigh:
- scores.append(float(tScores[count]))
- labels.append(tLabels[count]+' '+str(round(float(tScores[count])*100, 2))+'%')
- boxes.append ([x0, y0, x1, y1])
- displayBoxedImage(image, boxes, labels)
-
-#### Live Detection
-def detectLive(model, showSight = True):
- gbx = 0
- gby = 0
- dist = 0
-
- header = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.159 Safari/537.36."}
- req = Request(url, headers=header)
- img_resp = urlopen(req, timeout=60)
- imgnp=np.array(bytearray(img_resp.read()),dtype=np.uint8)
- frame=cv2.imdecode(imgnp,-1)
-
- labels, boxes, scores = model.predict(frame)
- for i in range(boxes.shape[0]):
- box = boxes[i]
- x0, y0 = float(box[0]), float(box[1])
- x1, y1 = float(box[2]), float(box[3])
- w = x1 - x0
- h = y1 - y0
- dCrop = [int(y0*cropFactor + y1*(1-cropFactor)), int(y1*cropFactor + y0*(1-cropFactor)),
- int(x0*cropFactor + x1*(1-cropFactor)), int(x1*cropFactor + x0*(1-cropFactor))]
- avgClRGB = cv2.mean(frame[dCrop[0]:dCrop[1], dCrop[2]:dCrop[3]])
- avgClHue = rgbToHue(avgClRGB)
-
- if scores[i] > minDetectionScore and avgClHue > colorLow and avgClHue < colorHigh:
- cv2.rectangle(frame, (int(x0), int(y0)),
- (int(x1), int(y1)),
- (0, 255, 0), 2)
- if labels:
- dist = distanceDetect('load-testImg', distWtsFile, [[x0, x1, y0, y1], frame.shape[:2]])
- gbx = int((x1 + x0) / 2)
- gby = int((y1 + y0) / 2)
- cv2.putText(frame, 'x:{}, y:{}'.format(gbx, gby),
- (int(box[0]), int(box[1]) - 10),
- cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 3)
-
-
- cv2.imshow('Ball Detection', frame)
- key = cv2.waitKey(1) & 0xFF
- return gbx, gby,dist
-
-### Supplementary Functions
-#### Display of Image with Bounding Boxes
-def displayBoxedImage(image, boxes = [], labels = None):
- fig, ax = plt.subplots(1)
- if isinstance(image, torch.Tensor):
- image = utils.reverse_normalize(image)
- image = transforms.ToPILImage()(image)
- ax.imshow(image)
- if labels is not None and not utils._is_iterable(labels):
- labels = [labels]
- for i in range(len(boxes)):
- box = boxes[i]
- width, height = box[2] - box[0], box[3] - box[1]
- initial_pos = (box[0], box[1])
- rect = patches.Rectangle(initial_pos, width, height, linewidth = 1, edgecolor = 'r', facecolor = 'none')
- if labels:
- ax.text(box[0] + 5, box[1] - 5, '{}'.format(labels[i]), color='red')
- ax.add_patch(rect)
- plt.show()
-
-#### Calculation of Hue from RGB (adopted from [code](https://www.geeksforgeeks.org/program-change-rgb-color-model-hsv-color-model/))
-def rgbToHue(RGB):
- RGB = [val/255.0 for val in RGB]
- cmax = max(RGB)
- cmin = min(RGB)
- diff = cmax - cmin
- r, g, b = RGB[0:3]
- if cmax == cmin:
- return 0
- if cmax == r:
- return (60 * ((g - b) / diff) + 360) % 360
- if cmax == g:
- return (60 * ((b - r) / diff) + 120) % 360
- if cmax == b:
- return (60 * ((r - g) / diff) + 240) % 360
-
-#### Formula-based Depth Estimation (adopted from [mono_depth.py](https://github.com/agrawalparth10/FORAY-Perception/blob/master/mono_depth/mono_depth.py))
-def depth_estimate(figDims, boundingBox):
- def x_hat(realLen, ip, i0, imageLen):
- return (realLen * (ip-i0)) / imageLen
- def y_hat(realLen, jp, j0, imageLen):
- return (realLen * (jp-j0)) / imageLen
- def z_hat(dist, pixelLen, imageLen):
- return dist*(pixelLen/imageLen)
- def cal_coordinates(dist, realLen, ip, jp, i0, j0, imageLen, pixelLen):
- return (x_hat(realLen, ip, i0, imageLen), y_hat(realLen, jp, j0, imageLen), z_hat(dist, pixelLen, imageLen))
- def measure(dist, realLen, ip, jp, i0, j0, imageLen, pixelLen):
- x_cor = x_hat(realLen, ip, i0, imageLen)
- z_cor = z_hat(dist, pixelLen, imageLen)
- dist = (x_cor ** 2 + z_cor ** 2) ** 0.5
- return dist
- imHeight, imWidth = figDims
- center = (imWidth // 2, imHeight // 2)
- x, y, w, h = boundingBox[0:4]
- relativeDist = measure (dist = 0.51, realLen = 0.228, ip = x, jp = y, i0 = center[0], j0 = center[1], imageLen = w, pixelLen = 500)
- coordinates = cal_coordinates(dist = 0.51, realLen = 0.228, ip = x, jp = y, i0 = center[0], j0 = center[1], imageLen = w, pixelLen = 500)
- return relativeDist, coordinates
-
-### Declare Varables and Constants
-device = 'cuda'
-imageLoc = './ball_detection/images/train-test-4/' #
-labelSet = ['ball']
-modelLoc = './ball_detection/model_weights/' #
-trainLoc = imageLoc + 'train/'
-colorLow = 60
-colorHigh = 180
-modelFile = 'model_weights-2-20210818_002355-cpu.pth'
-modelname = modelName(int(modelFile[14]))
-modelType = 2
-cropFactor = 0.90
-distWtsFile = './ball_detection/distance-detection-torch/distance-detection-weights-3-2.0sd-20210808_212550.json'
-modelAction = 'load' # 'load' to load previous model, 'new' to train new model (only possible on Colab)
-
-#FOR THE NEXT LINE : UNCOMMENT the first time you run, COMMENT OUT after the first time
-modifyCore()
-#########
-
-# model = returnModel(modelAction, device, trainLoc, labelSet, modelLoc, modelFile)
-# # # ## Testing (using Live Streaming)
-# while True:
-# detectLive(model)
-
-# ## Testing (using Untrained Images)
-# for file in sorted(glob.glob(imageLoc + '/test/*.jpg')):
-# objectDetection(file)
-#
-# ## Evaluation (using Trained Images)
-# for file in sorted(glob.glob(imageLoc + '/train/*.jpg')):
-# objectDetection(file)
diff --git a/Code/Control/Laptop_Code/constants.py b/Code/Control/Laptop_Code/constants.py
index 9c7c47bd4b54c1f04a243ba48dd0bfd7d372fcfe..add5d84528a380888d352f57cffcb3030d33dd1a 100644
--- a/Code/Control/Laptop_Code/constants.py
+++ b/Code/Control/Laptop_Code/constants.py
@@ -31,11 +31,10 @@ Bmax = 127
threshold = [Lmin, Lmax, Amin, Amax, Bmin, Bmax]
base_speed = 120
-seeking_speed = 70
+seeking_speed = 50
LIDAR_Thres = 300 # mm
-
# PID Control in move2ball
kpx,kix,kdx = 1.2, 0.01, 0.5
# kpx,kix,kdx = 0.0, 0.00, 0.0
@@ -44,14 +43,21 @@ kpy,kiy,kdy = 1.2, 0.05, 0.9
# PID Control in move2goal
# kpx_g,kix_g,kdx_g = 1.5, 0.01, 0.5
-kpx_g,kix_g,kdx_g = 2, 0.01, 0.7
+kpx_g,kix_g,kdx_g = 1.6, 0.01, 0.7
# kpx_g,kix_g,kdx_g = 0.0, 0.0, 0.0
-kpy_g,kiy_g,kdy_g = 1.7, 0.01, 0.7
+kpy_g,kiy_g,kdy_g = 2, 0.01, 0.7
# kpy_g,kiy_g,kdy_g = 0.0, 0.0, 0.0
# difference between center of AT and center of goal
AT_goal_Delta = 0 #cm
-AT_h1 = 50 # meters
+AT_h1 = 140 # openmv: | esp32_cam:meters
+
+kph,kih,kdh = 1.2,0.01,0.5
+
+# Break between AT detection during ball seeking
+AT_detectBreak = 60
+
+
-kph,kih,kdh = 1.2,0.01,0.5
\ No newline at end of file
+url_gb = 'http://10.0.0.5/cam-hi.jpg' #01
diff --git a/Code/Control/Laptop_Code/imageThread_AT_gb_1_6.py b/Code/Control/Laptop_Code/imageThread_AT_gb_1_6.py
new file mode 100644
index 0000000000000000000000000000000000000000..c38b498ce6ce7282a558f7cdc51a4b1f1c9933fa
--- /dev/null
+++ b/Code/Control/Laptop_Code/imageThread_AT_gb_1_6.py
@@ -0,0 +1,38 @@
+# import sys
+# sys.path.append("../")
+
+from ESP32_AT.imageTread_AT import get_AT_6DOF_info
+
+from constants import *
+import ball_detection.ball_detection as ball_detection
+import cv2
+
+# detector = apriltag.Detector()
+
+
+if __name__ == "__main__":
+ url_AT = 'http://10.0.0.9/cam-hi.jpg' #6
+ url_gb = 'http://10.0.0.5/cam-hi.jpg' #1
+
+ tid,tx,ty,tz,rx,ry,rz = 0,0,0,0,0,0,0
+
+ # GB
+ ball_detection.modifyCore()
+ # modelLoc = './ball_detection/model_weights/'
+ # modelFile = 'model_weights-2-20210818_002355-cpu.pth'
+ model = ball_detection.returnModel(device, labelSet, modelLoc, modelFile)
+
+ gbx, gby = -1, -1 # by default (-1 means no found green ball)
+ gb_dist = -1 # by default (-1 means no found green ball)
+
+
+ while True:
+ tid,tx,ty,tz,rx,ry,rz = get_AT_6DOF_info(url_AT)
+
+ # gbx, gby, gb_dist = ball_detection.detectLive(url_gb, model, minDetectionScore, showSight = True)
+
+ key=cv2.waitKey(5)
+ if key==ord('q'):
+ break
+
+ cv2.destroyAllWindows()
diff --git a/Code/Control/Laptop_Code/imageThread_AT_gb.py b/Code/Control/Laptop_Code/imageThread_AT_gb_2_4.py
similarity index 75%
rename from Code/Control/Laptop_Code/imageThread_AT_gb.py
rename to Code/Control/Laptop_Code/imageThread_AT_gb_2_4.py
index fde64ac8e5d881978b58d3bd82a4cb24d13a791c..62ffb17295f372259451b2dc2030c6303d368906 100644
--- a/Code/Control/Laptop_Code/imageThread_AT_gb.py
+++ b/Code/Control/Laptop_Code/imageThread_AT_gb_2_4.py
@@ -11,8 +11,8 @@ import cv2
if __name__ == "__main__":
- url1 = 'http://192.168.0.230/cam-hi.jpg'
- url2 = 'http://192.168.0.204/cam-hi.jpg'
+ url_AT = 'http://10.0.0.3/cam-hi.jpg' #2
+ url_gb = 'http://10.0.0.6/cam-hi.jpg' #4
tid,tx,ty,tz,rx,ry,rz = 0,0,0,0,0,0,0
@@ -28,9 +28,9 @@ if __name__ == "__main__":
while True:
- tid,tx,ty,tz,rx,ry,rz = get_AT_6DOF_info(url1)
+ tid,tx,ty,tz,rx,ry,rz = get_AT_6DOF_info(url_AT)
- gbx, gby, gb_dist = ball_detection.detectLive(model, minDetectionScore, showSight = True)
+ # gbx, gby, gb_dist = ball_detection.detectLive(url_gb, model, minDetectionScore, showSight = True)
key=cv2.waitKey(5)
if key==ord('q'):
diff --git a/Code/Control/Laptop_Code/main_keyboard.py b/Code/Control/Laptop_Code/main_keyboard.py
index e709ad57f84b34abe946a024c72fcf7b28066f61..d1436398643b6c480532b27dc32979af53441a32 100644
--- a/Code/Control/Laptop_Code/main_keyboard.py
+++ b/Code/Control/Laptop_Code/main_keyboard.py
@@ -8,9 +8,11 @@ from constants import *
from ESP32_AT.imageTread_AT import get_AT_6DOF_info
global ml,esp_cam_on,openmv_on
-ml = 1
-esp_cam_on = 0
-openmv_on = 1
+ml = 0
+esp_cam_on = 1
+openmv_on = 0
+seekVertDir = 1
+AT_detected_time = time.time()
if ml == 1:
import ball_detection.ball_detection as ball_detection
@@ -31,7 +33,7 @@ def serial_port_in_v1(serial_port):
# DEBUG Verbose
print("initiating one round of serial in ...")
- for i in range(8):
+ for i in range(7):
line = serial_port.readline()
val = int(line.decode())
@@ -49,9 +51,10 @@ def serial_port_in_v1(serial_port):
rz = val
elif i == 6:
LIDAR_dist1 = val
- elif i == 7:
- LIDAR_dist2 = val
+ # elif i == 7:
+ # LIDAR_dist2 = val
+ LIDAR_dist2 = 0
line = serial_port.readline()
debugM = line.decode()
@@ -190,16 +193,17 @@ def move2goal(tx, ty,tz):
setpoint_x1 = 0.0
setpoint_y1 = 0.0
- if tz <200:
- kpy_g,kiy_g,kdy_g = 0.0, 0.0, 0.0
- base_speed = 150
- AT_goal_Delta = 150
+ if tz < 2.0:
+ kpy_g,kiy_g,kdy_g = 2, 0.1, 0.5
+ base_speed = 200
+ AT_goal_Delta = -150
else:
- kpy_g,kiy_g,kdy_g = 2, 0.01, 0.5
- base_speed = 120
+ kpy_g,kiy_g,kdy_g = 2, 0.1, 0.5
+ # kpy_g,kiy_g,kdy_g = 0.0, 0.00, 0.0
+ base_speed = 140
AT_goal_Delta = 0
- inputx = tx / 1.00
- inputy = (ty + AT_goal_Delta) / 1.00 #
+ inputx = tx * 100/ 1.00
+ inputy = (ty * 100 + AT_goal_Delta) / 1.00 #
pid_x = PID(kpx_g, kix_g, kdx_g, setpoint = setpoint_x1)
pid_y = PID(kpy_g, kiy_g, kdy_g, setpoint = setpoint_y1)
@@ -211,17 +215,17 @@ def move2goal(tx, ty,tz):
outputx = pid_x(inputx)
outputy = pid_y(inputy)
-
+ print("outputy:{}".format(outputy))
# Vertical
pwm1 = abs(outputy)
pwm2 = abs(outputy)
if(outputy > 0):
- dir1 = '-'
- dir2 = '-'
- else:
dir1 = '+'
dir2 = '+'
+ else:
+ dir1 = '-'
+ dir2 = '-'
# Horizontal
lspeed = -1 * outputx + base_speed
@@ -253,9 +257,9 @@ def ball_seeking(count_h,tx,ty):
pwm1, pwm2, pwm3, pwm4
dir1, dir2, dir3, dir4
"""
- global set_h
+ global set_h, seekVertDir
if openmv_on == 1:
- delta_h = 100
+ delta_h = 100 # cm
threshold_h = 20
elif esp_cam_on == 1:
delta_h = 2 # meter
@@ -282,6 +286,23 @@ def ball_seeking(count_h,tx,ty):
else:
pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = rotate_one_direction()
+
+ # if time.time() > AT_detected_time + AT_detectBreak:
+ # AT_detected = AT_detect(tx, ty)
+ # AT_detected_time = time.time()
+ #
+ # while facingWall():
+ # pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = rotate_one_direction_ssp(new_ssp)
+ #
+ # if AT_detected:
+ # current_h = get_altitude_from_AT(AT_h1,ty)
+ #
+ # if LIDAR_dist2 < LIDAR2_Thres:
+ # seekVertDir = 0
+ # if baroHeight < baroThres:
+ # seekVertDir = 1
+ # pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = move_in_spiral(new_ssp, seekVertDir)
+
return int(pwm1), int(pwm2), int(pwm3), int(pwm4), dir1, dir2, dir3, dir4
def vertical_control(current_h,set_h):
@@ -317,6 +338,14 @@ def rotate_one_direction_ssp(ssp):
return int(pwm1), int(pwm2), int(pwm3), int(pwm4), dir1, dir2, dir3, dir4
+def move_in_spiral(ssp, dir):
+ pwm1, pwm2, pwm3, pwm4 = ssp, ssp, ssp, ssp/2
+ dir1, dir2, dir3, dir4 = '+', '+', '+', '-'
+ if dir == 0:
+ dir1, dir2 = '-', '-'
+
+ return int(pwm1), int(pwm2), int(pwm3), int(pwm4), dir1, dir2, dir3, dir4
+
def move2ball(gbx, gby, gb_dist):
"""
Description:
@@ -394,6 +423,7 @@ def main_control(gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_d
Output:
pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 : Blimp motor manuver parameters
'''
+ print('in main_control')
# placeholder
pwm1, pwm2, pwm3, pwm4 = 0 , 0 , 0 , 0
dir1, dir2, dir3, dir4 = '+', '-', '+', '-'
@@ -402,12 +432,14 @@ def main_control(gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_d
ballCapture = ball_capture(LIDAR_dist1)
goalDetect = goal_detect(tx, ty)
- ballCapture = 1
+ ballCapture = 0
# debug
- # ballCapture = 1
+ ballCapture = 1
# goalDetect = 0
+ # ballDetect = 0
if ballCapture: # Ball captured
+ print('ballCapture TRUE')
if goalDetect: # Goal detected
# stop_all() # Debug
pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = move2goal(tx, ty,tz)
@@ -415,21 +447,24 @@ def main_control(gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_d
# stop_all() # Debug
pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = rotate_one_direction()
else: # Ball not captured
+ print('ballCapture FALSE')
if ballDetect: # Ball detected
pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = move2ball(gbx,gby,gb_dist)
else: # Ball not detected
# stop_all() # Debug
- # pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = rotate_one_direction()
- pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = ball_seeking(count_h,tx,ty)
+ pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = rotate_one_direction()
+
+ # pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = ball_seeking(count_h,tx,ty)
return pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4
def auto_control(serial_port,gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_dist2, debugM,count_h):
# ===== STEP 1: TAKE ALL INPUT =====
+ # print('in auto_control')
if ml ==1:
- gbx, gby, gb_dist = ball_detection.detectLive(model, minDetectionScore, showSight = True)
+ gbx, gby, gb_dist = ball_detection.detectLive(url_gb, model, minDetectionScore, showSight = True)
line = serial_port.readline()
-
+ # print('auto')
if openmv_on == 1:
if line == b'SERIAL_IN_START\r\n':
tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_dist2, debugM = serial_port_in_v1(serial_port)
@@ -438,8 +473,12 @@ def auto_control(serial_port,gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_di
if esp_cam_on == 1:
- url = 'http://192.168.1.118/cam-hi.jpg'
+ url = 'http://192.168.0.204/cam-hi.jpg'
tid, tx, ty, tz, rx, ry, rz = get_AT_6DOF_info(url)
+ LIDAR_dist1 = 0
+ LIDAR_dist2 = 0
+ debugM = "using two esp32 cam"
+
# ===== STEP 2: MAIN CONTROL LOOP =====
pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = main_control(gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_dist2,
@@ -452,7 +491,7 @@ def auto_control(serial_port,gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_di
def auto_init(init_count,gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_dist2, debugM):
count_h = 0
- # gbx, gby, gb_dist = ball_detection.detectLive(model, minDetectionScore, showSight = True)
+ # gbx, gby, gb_dist = ball_detection.detectLive(url_gb, model, minDetectionScore, showSight = True)
pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = main_control(gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_dist2, debugM, count_h)
serial_port_out(serial_port, pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4)
init_count += 1
@@ -572,7 +611,7 @@ def manual_control(Ctl_com,serial_port):
waitTime = 0.05
# changed
- # gbx, gby, gb_dist = ball_detection.detectLive(model, minDetectionScore, showSight = True)
+ # gbx, gby, gb_dist = ball_detection.detectLive(url_gb, model, minDetectionScore, showSight = True)
serial_port_out(serial_port, pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4)
@@ -606,8 +645,21 @@ def get_altitude_from_AT(AT_h,ty):
altitude = AT_h - ty
return altitude
+
+
def test_function():
- url = 'http://192.168.1.118/cam-hi.jpg'
+ url = 'http://192.168.0.230/cam-hi.jpg'
+ tid, tx, ty, tz, rx, ry, rz = get_AT_6DOF_info(url)
+ print("testing new function")
+ print("-----------------------")
+ print("tid:{}".format(tid))
+ print("tx,ty,tz:{},{},{}".format(tx,ty,tz))
+ print("rx,ry,rz:{},{},{}".format(rx,ry,rz))
+
+
+
+def test_function1():
+ url = 'http://192.168.0.230/cam-hi.jpg'
tid, tx, ty, tz, rx, ry, rz = get_AT_6DOF_info(url)
print("testing new function")
print("-----------------------")
@@ -616,6 +668,7 @@ def test_function():
print("rx,ry,rz:{},{},{}".format(rx,ry,rz))
+
# ===== Main Function =====
if __name__ == '__main__':
# =========== SET UP ============
@@ -651,7 +704,7 @@ if __name__ == '__main__':
Ctl_com = [0, 0, 0, 0, "+", "+", "+", "+"]
# Trigger the ESP32_SLAVE to talk first
"""
- gbx, gby, gb_dist = ball_detection.detectLive(model, minDetectionScore, showSight = True)
+ gbx, gby, gb_dist = ball_detection.detectLive(url_gb, model, minDetectionScore, showSight = True)
pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4 = main_control(gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_dist2, debugM, count_h)
serial_port_out(serial_port, pwm1, pwm2, pwm3, pwm4, dir1, dir2, dir3, dir4)
"""
@@ -669,6 +722,7 @@ if __name__ == '__main__':
while (flag == 1):
if init_count == 0:
init_count,count_h = auto_init(init_count,gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_dist2, debugM)
+ print('auto_control')
auto_control(serial_port,gbx, gby, gb_dist, tx, ty, tz, rx, ry, rz, LIDAR_dist1, LIDAR_dist2, debugM,count_h)
flag, print_count = keyboard_stop(flag,print_count)
elif get_key('s'):
diff --git a/Code/ESP32_Cam/WifiCam/WifiCam.ino b/Code/ESP32_Cam/WifiCam/WifiCam.ino
index 6515ca9d1834f969bc466cf54edd0ac5300dd85b..ef9e520b37486e33033bac5aa344f183057c7d83 100644
--- a/Code/ESP32_Cam/WifiCam/WifiCam.ino
+++ b/Code/ESP32_Cam/WifiCam/WifiCam.ino
@@ -3,8 +3,14 @@
#include <esp32cam.h>
-const char* WIFI_SSID = "lemur";
-const char* WIFI_PASS = "lemur9473";
+// const char* WIFI_SSID = "lemur";
+// const char* WIFI_PASS = "lemur9473";
+
+// const char* WIFI_SSID = "uclahci";
+// const char* WIFI_PASS = "94739473";
+
+const char* WIFI_SSID = "NETGEAR33";
+const char* WIFI_PASS = "freestreet163";
// const char* WIFI_SSID = "LEMUR_ESP32_EYE_AP_1";
// const char* WIFI_PASS = "123456789";