Merge branch 'main' of https://github.com/raiots/USVLander

.gitignore

@@ -0,0 +1,197 @@
+# Created by https://www.toptal.com/developers/gitignore/api/python,visualstudiocode
+# Edit at https://www.toptal.com/developers/gitignore?templates=python,visualstudiocode
+
+### Python ###
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
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+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
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+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
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+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
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+
+# Django stuff:
+*.log
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+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
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+.scrapy
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+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
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+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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+
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+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
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+
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+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+### Python Patch ###
+# Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration
+poetry.toml
+
+# ruff
+.ruff_cache/
+
+# LSP config files
+pyrightconfig.json
+
+### VisualStudioCode ###
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
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+!.vscode/extensions.json
+!.vscode/*.code-snippets
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+# Built Visual Studio Code Extensions
+*.vsix
+
+### VisualStudioCode Patch ###
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+.history
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+
+data/
+
+# End of https://www.toptal.com/developers/gitignore/api/python,visualstudiocode

README.md

@@ -0,0 +1,29 @@
+# USVLander
+
+## 项目介绍
+USVLander 是一个完全基于计算机视觉的无人机控制算法，目前针对 DJI Tello 无人机设计，能够实现视觉自主降落至无人船。该项目基于 Python 编程语言，并集成了 YOLO 实时目标检测系统和 OpenCV 计算机视觉库，以提供精确的导航和控制。
+
+## 安装说明
+要安装 USVLander，您需要确保您的系统中已安装 Python 3.10 或更高版本（开发过程基于 Python3.10.8 ）。此外，您还需要安装 YOLO 和 OpenCV 库。可以通过以下命令安装所需的依赖项：
+
+```bash
+pip install -r requirements.txt
+```
+
+## 如何使用
+在安装所有必要的依赖项后，您可以通过以下步骤使用 USVLander 控制算法：
+
+1. 将无人机与您的计算机连接。
+2. 打开终端并导航到 USVLander 项目目录。
+3. 运行主控制脚本：
+
+```bash
+python main.py
+```
+
+## License
+USVLander 根据 MIT 许可证发布。这意味着您可以自由地使用、修改和分发该软件，但您必须包含原始作者的版权声明和许可声明。
+
+请注意，此 README 是一个基本模板，您可能需要根据项目的具体情况进行调整。确保在发布之前，您已经完全测试了所有的功能，并且代码的文档是最新的。祝您的项目成功！
+![alt text](docs\Draft_process.png)
+

agent.py

@@ -6,9 +6,9 @@ import sys
 import time
 import logging
 import cv2
-
+import numpy as np
 from control import ManualControl, AutoControl
-from control import Status
+from utils import Status, DataRecorder
 
 
 
@@ -20,6 +20,11 @@ class UAV:
         self.tello.connect()
         print('Current_battery: ' + str(self.tello.get_battery()))
         self.tello.streamon()
+        self.tello.set_video_resolution(Tello.RESOLUTION_480P)
+        self.tello.set_video_fps(Tello.FPS_30)
+        self.tello.set_video_bitrate(Tello.BITRATE_1MBPS)
+        self.tello.set_video_direction(Tello.CAMERA_FORWARD)
+
         self.frame_read = self.tello.get_frame_read()
 
         self.left_right_velocity = 0
@@ -33,51 +38,77 @@ class UAV:
         self.status = Status.DETECT
 
         self.frame_queue = Queue(maxsize=1)  # 用于存放视频帧, 1用于避免帧堆积
+        record_name = input("请输入数据备注（英文）:")
+        if record_name:
+            self.recorder = DataRecorder(exp_note=record_name, need_record=True)
+        else:
+            self.recorder = DataRecorder()
+
+        self.front_cam_shape = (648, 478)  # x, y
     
     def update(self):
         """ Update routine. Send velocities to Tello.
 
             向Tello发送各方向速度信息
         """
+        if self.yaw_velocity > 50:
+            self.yaw_velocity = 50
+        elif self.yaw_velocity < -50:
+            self.yaw_velocity = -50
+            
         if self.send_rc_control:
             self.tello.send_rc_control(self.left_right_velocity, self.for_back_velocity,
                 self.up_down_velocity, self.yaw_velocity)
-    
+        print(self.left_right_velocity, self.for_back_velocity,
+            self.up_down_velocity, self.yaw_velocity)
+
     def run(self):
         """ 主程序 """
-        # self.init_flight()
+        self.init_flight()
+        # self.tello.turn_motor_on()
 
         state_thread = Thread(target=self.video_stream)
         state_thread.start()
 
-        # self.send_rc_control = True
-        # self.manual_control.start()  # 启动手动控制键盘监听
+        self.manual_control.start()  # 启动手动控制键盘监听
 
         while True:
             # self.up_down_velocity(10)
-            # self.send_rc_control = True
-            self.auto_control()
+            self.auto_track_land()
             self.update()
-            self.video_display()
+            # self.video_display()
             time.sleep(0.05)
 
     def signal_handler(self, signal, frame):
         print ('\nSignal Catched! 执行急停！')
         self.tello.emergency()
+        self.tello.streamoff()
         sys.exit(0)
 
     def init_flight(self):
         self.tello.turn_motor_on()
-        time.sleep(10)
+        time.sleep(5)
         logging.warn('自检完毕，可以起飞')
         self.tello.takeoff()
+        self.send_rc_control = True  # 开启发送控制信号
+        self.update()
+        self.tello.go_xyz_speed(0, 0, 50, 20)  # 初始升高高度
 
     def video_stream(self):
+        # 独立线程，用于获取视频流并记录状态
         height, width, _ = self.frame_read.frame.shape
         while True:
             frame = self.frame_read.frame
             self.frame_queue.put(frame)
 
+            states = self.tello.get_current_state()
+            states['timestamp'] = time.time()
+            states['status'] = self.status
+            states['cmd_vel'] = [self.left_right_velocity, self.for_back_velocity, self.up_down_velocity, self.yaw_velocity]
+            
+            self.recorder.state_record(states)
+            self.recorder.frame_record(frame, 'origin')
+
             time.sleep(1 / 30)
 
     def video_display(self):
@@ -88,20 +119,31 @@ class UAV:
             if cv2.waitKey(1) & 0xFF == ord('q'):
                 self.keep_recording = False
                 cv2.destroyAllWindows()
+            if cv2.waitKey(1) & 0xFF == ord('s'):
+                cv2.imwrite(str(time.time()) + '.jpg', frame)
 
     def auto_track_land(self):
+        # print(self.status)
 
-        if self.status == Status.INIT or self.status == Status.TRACKING:
+        if self.status == Status.TRACK or self.status == Status.DETECT:
             front_img = self.frame_queue.get()
+            front_img = cv2.cvtColor(front_img, cv2.COLOR_RGB2BGR)
             if self.status == Status.DETECT:
                 self.auto_control.detect(front_img=front_img)
             elif self.status == Status.TRACK:
                 self.auto_control.track(front_img=front_img)
+        
+        elif self.status == Status.LANDING:
+            bottom_img = self.frame_queue.get()
+            self.auto_control.landing(bottom_img=bottom_img)
+
+        elif self.status == Status.FALLING:
+            # 自由落体阶段
+            pass
+        time.sleep(1 / 30)
 
         
             
 if __name__ == '__main__':
     uav = UAV()
-    # while True:
-    #     print(uav.tello.get_current_state())
     uav.run()

control.py

@@ -1,20 +1,18 @@
 from pynput import keyboard
 import time
-
+import logging
 from vision import Tracker
 import cv2
-from enum import Enum
+from utils import Status
+import pupil_apriltags as apriltag
+from djitellopy import Tello
 
 
 
 TICKS_PER_SEC = 30
 
 
-class Status(Enum):
-    INIT = 0
-    DETECT = 1
-    TRACK = 2
-    LANDING = 3
+
 
 class PIDController:
     def __init__(self, kp, ki, kd, current_time):
@@ -25,7 +23,7 @@ class PIDController:
         self.integral = 0
         self.last_time = current_time
 
-    def control(self, error, current_time):
+    def control(self, error, current_time) -> int:
         current_time = current_time
         delta_time = current_time - self.last_time
         if delta_time == 0:
@@ -38,7 +36,7 @@ class PIDController:
         self.previous_error = error
         self.last_time = current_time
 
-        return output
+        return int(output)
 
 
 class ManualControl:
@@ -63,10 +61,12 @@ class ManualControl:
                 self.uav.up_down_velocity = 50
             elif key.char == 's':
                 self.uav.up_down_velocity = -50
-            elif key.char == 'q':
+            elif key.char == 'z':
                 self.uav.yaw_velocity = -50
-            elif key.char == 'e':
+            elif key.char == 'c':
                 self.uav.yaw_velocity = 50
+            elif key.char == 'l':
+                self.uav.tello.land()
             # print(f'left_right_velocity: {self.uav.left_right_velocity}, for_back_velocity: {self.uav.for_back_velocity}, up_down_velocity: {self.uav.up_down_velocity}, yaw_velocity: {self.uav.yaw_velocity}')
         except AttributeError:
             pass
@@ -79,7 +79,7 @@ class ManualControl:
                 self.uav.left_right_velocity = 0
             elif key.char == 'w' or key.char == 's':
                 self.uav.up_down_velocity = 0
-            elif key.char == 'q' or key.char == 'e':
+            elif key.char == 'z' or key.char == 'c':
                 self.uav.yaw_velocity = 0
         except AttributeError:
             pass
@@ -89,27 +89,132 @@ class AutoControl:
     def __init__(self, uav):
         self.uav = uav
         self.target = [0, 0, 0, 0]
-        self.pid = PIDController(1, 0, 0, time.time())
+        self.tag_detector = apriltag.Detector(families='tag36h11')
+
+        self.yaw_controller = PIDController(0.3, 0, 0.1, time.time())
+        self.for_back_controler = PIDController(100, 0, 0.1, time.time())
+        self.left_right_controler = PIDController(50, 0, 0.1, time.time())  # 摄像头左右视野较小
+        self.loss_target_times = 0
+        self.is_get_tag = False
+        self.get_tag_times = 0
 
     def detect(self, front_img):
-        cv2.imshow("ROI select", front_img[:, :, 0:3])
-        self.gROI = cv2.selectROI("ROI select", front_img[:, :, 0:3], False)
+        cv2.imshow("ROI select", front_img)
+
+        # 在 selectROI 前等待按键（可选）
+        key = cv2.waitKey(10)  # 等待按键
+        if key == ord('q'):  # 如果按下 'q' 键
+            print("Quit selected before ROI.")
+            self.uav.tello.land()
+            cv2.destroyAllWindows()
+            exit()
+
+        self.gROI = cv2.selectROI("ROI select", front_img, False)
         if (not self.gROI):
             print("空框选，退出")
-            quit()
+            self.uav.tello.land()
         self.gTracker = Tracker(tracker_type="KCF")
-        self.gTracker.initWorking(front_img[:, :, 0:3], self.gROI)
-        print("start tracking")
+        self.gTracker.initWorking(front_img, self.gROI)
+        logging.info("start tracking")
         self.uav.status = Status.TRACK
         cv2.destroyWindow("ROI select")
 
-    def track(self, front_img):
+    def track(self, front_img):        
         _item = self.gTracker.track(front_img)
-        if _item.message:
+        if _item.getMessage():
+            self.loss_target_times = 0
+            logging.info('tracking')
             self.target = _item.getMessage()['target']
+            # print(self.target)
+            target_dict  = {'timestamp': time.time(), 'x': self.target[0], 'y':self.target[1]}
+            self.uav.recorder.anything_record(target_dict, 'track_result', ['timestamp', 'x', 'y'])
+            
+            frame = _item.getFrame()
+            cv2.imshow("track result", frame)
+            self.uav.recorder.frame_record(frame, 'KCF_tracking')
+
+            # store the frame to video
+
+            _key = cv2.waitKey(1) & 0xFF
+            if (_key == ord('q')) | (_key == 27):
+                self.uav.status = Status.LANDING
+            
+            if (_key == ord('r')) :
+                self.uav.status = Status.DETECT
+            # print(_item.getFrame())
+            # print(self.target)
+            yaw_vel = self.yaw_controller.control(self.target[0] - self.uav.front_cam_shape[0]/2, time.time())
+            self.uav.yaw_velocity = int(yaw_vel)
+            self.uav.for_back_velocity = 20
             
         else:
-            return None
+            self.loss_target_times += 1
+            if self.loss_target_times == 6:
+                # 等待6帧（0.2秒），仍丢失则重新检测并重置计数器
+                self.loss_target_times = 0  # 在函数头部还有一个
+                self.uav.status = Status.DETECT
+                self.uav.yaw_velocity = 0
+                self.uav.for_back_velocity = 0
+        
+        if self.target[1] > self.uav.front_cam_shape[1] * 0.8:
+            print(self.target[1], self.uav.front_cam_shape[0]/10)
+            logging.warn("ready to land")
+            self.uav.yaw_velocity = 0
+            self.uav.for_back_velocity = 10
+            self.uav.status = Status.LANDING
+            self.uav.tello.set_video_direction(Tello.CAMERA_DOWNWARD)
+            cv2.destroyAllWindows()
+            time.sleep(1)  # 等待1秒，确保摄像头回传到位
+
+    def landing(self, bottom_img):
+        tag_large = self.tag_detector.detect(bottom_img[:, :, 0], estimate_tag_pose=True, camera_params=([353.836278849487, 353.077028029136, 163.745870517989, 115.130883974855]), tag_size=0.169)
+        tag_small = self.tag_detector.detect(bottom_img[:, :, 0], estimate_tag_pose=True, camera_params=([353.836278849487, 353.077028029136, 163.745870517989, 115.130883974855]), tag_size=0.018)
+        tag_list = []
+        for tag in tag_large:
+            if tag.tag_id == 1:
+                tag_list.append(tag)
+        for tag in tag_small:
+            if tag.tag_id == 0:
+                tag_list.append(tag)
+
+        if tag_list:
+            # 如果检测到标签
+            self.get_tag_times += 1
+            if self.get_tag_times >= 5:
+                # 检测到5次后才认为大部分tag已经进入视野
+                self.is_get_tag = True
+
+                for_vel = -1 * self.for_back_controler.control(tag_list[0].pose_t[0], time.time())
+                self.uav.for_back_velocity = int(for_vel)
+
+                left_vel = -1 * self.left_right_controler.control(tag_list[0].pose_t[1], time.time())
+                self.uav.left_right_velocity = int(left_vel)
+                # print(self.uav.for_back_velocity, self.uav.left_right_velocity)
+                if tag_list[0].pose_t[0] < 0.2 and tag_list[0].pose_t[1] < 0.2:
+                    self.uav.up_down_velocity = -20
+                # print(tag_list[0].pose_t)  # 后正左正高度
+                if tag_list[0].pose_t[2] < 0.3:
+                    self.uav.tello.land()
+                    self.uav.status = Status.FALLING
+        else:
+            self.uav.up_down_velocity = 0
+            self.uav.left_right_velocity = 0
+            if self.is_get_tag:
+                self.uav.for_back_velocity = 0
+                logging.warn("no tag detected")
+
+        cv2.imshow('aa', bottom_img[:, :, 0])
+        cv2.waitKey(1)
+
+
+        # if tags:
+        #     self.uav.status = Status.LANDED
+        #     self.uav.tello.land()
+        #     logging.warn('landed')
+        # else:
+        #     self.uav.up_down_velocity = -20
+        
+        
 
 
 class FakeUAV:

test.py

@@ -0,0 +1,14 @@
+import pupil_apriltags as apriltag
+import cv2
+
+tag_detector = apriltag.Detector(families='tag36h11')
+
+img = cv2.imread('Snipaste_2024-06-22_21-30-43.png')
+# cv2.imshow('aaa', img)
+# print(img.shape)
+tag = tag_detector.detect(img[:,:,0], estimate_tag_pose=True, camera_params=([353.836278849487, 353.077028029136, 163.745870517989, 115.130883974855]), tag_size=0.018)
+
+for t in tag:
+    if t.tag_id == 0:
+        print(t.pose_t)
+        print(t.tag_id)

utils.py

@@ -0,0 +1,76 @@
+from enum import Enum
+from pathlib import Path
+from datetime import datetime
+import time
+import cv2
+import logging
+import csv
+
+
+class Status(Enum):
+    # INIT = 0
+    DETECT = 1
+    TRACK = 2
+    LANDING = 3
+    FALLING =  4
+
+class DataRecorder:
+    def __init__(self, exp_note='default', need_record=False):
+        # use path lib to manage file path
+        self.need_record = need_record
+        if need_record:
+            self.root_folder = Path('data') / str(datetime.now().strftime('%Y-%m-%d_%H-%M-%S') + '_' + exp_note)
+            self.root_folder.mkdir(parents=True, exist_ok=False)
+            self.video_folder = self.root_folder / 'video'
+            self.video_folder.mkdir(parents=True, exist_ok=False)
+
+            with open(str(self.root_folder) + '/sensor_data.csv', mode='a', newline='') as file:
+                writer = csv.DictWriter(file, fieldnames=['timestamp', 'mid', 'x', 'y', 'z', 'mpry', 'pitch', 'roll', 'yaw', 'vgx', 'vgy', 'vgz', 'templ', 'temph', 'tof', 'h', 'bat', 'baro', 'time', 'agx', 'agy', 'agz', 'status', 'cmd_vel'])
+                writer.writeheader()
+
+        else:
+            logging.warn("实验数据将不被记录！")
+
+    def frame_record(self, frame, cam_name:str):
+        if self.need_record:
+            cam_folder = self.video_folder / cam_name  # 分离不同来源的视频
+            if not cam_folder.exists():
+                # 如果文件夹不存在则创建
+                print('create folder:', str(cam_folder))
+                cam_folder.mkdir(parents=True, exist_ok=False)
+
+            frame_name = cam_folder / str(str(time.time()) + '.jpg')
+            if cv2.imwrite(str(frame_name), frame):
+                pass
+            else:
+                print('write frame failed')
+    
+    def state_record(self, states):
+        if self.need_record:
+            with open(str(self.root_folder) + '/sensor_data.csv', mode='a', newline='') as file:
+                writer = csv.DictWriter(file, fieldnames=['timestamp', 'mid', 'x', 'y', 'z', 'mpry', 'pitch', 'roll', 'yaw', 'vgx', 'vgy', 'vgz', 'templ', 'temph', 'tof', 'h', 'bat', 'baro', 'time', 'agx', 'agy', 'agz', 'status', 'cmd_vel'])
+                # writer.writeheader()
+                writer.writerow(states)
+
+    def anything_record(self, data, data_name:str, header:list):
+        if self.need_record:
+            with open(str(self.root_folder) + '/' + data_name + '.csv', mode='a', newline='') as file:
+                writer = csv.DictWriter(file, fieldnames=header)
+                # writer.writeheader()
+                writer.writerow(data)
+
+
+
+if __name__ == '__main__':
+    recorder = DataRecorder('aa')
+    # print(recorder.root_folder)
+    camera = cv2.VideoCapture(0)
+    while True:
+        ret, frame = camera.read()
+        if ret:
+            print(frame.shape)
+            cv2.imshow('frame', frame)
+            
+            recorder.frame_record(frame, 'front')
+            cv2.waitKey(1)
+        time.sleep(0.1)

vision.py

@@ -26,7 +26,7 @@ class Tracker(object):
         '''
         # 获得opencv版本
         (major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
-        self.tracker_types = ['BOOSTING', 'MIL', 'KCF', 'TLD', 'MEDIANFLOW', 'GOTURN']
+        self.tracker_types = ['BOOSTING', 'MIL', 'KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'CSRT']
         self.tracker_type = tracker_type
         self.isWorking = False
         self.draw_coord = draw_coord
@@ -46,6 +46,8 @@ class Tracker(object):
                 self.tracker = cv2.TrackerMedianFlow_create()
             if tracker_type == 'GOTURN':
                 self.tracker = cv2.TrackerGOTURN_create()
+            if tracker_type == 'CSRT':
+                self.tracker = cv2.TrackerCSRT_create()
  
     def initWorking(self, frame, box):
         '''