Havoc
3f35af954f
- 在task_2.py中引入异步箭头检测器，优化箭头方向检测流程，确保在关键路径点进行准确检测。 - 更新run_task_2函数以支持箭头方向的动态检测，并在任务执行中根据检测结果调整后续动作。 - 在task_4.py中添加run_task_4_back函数，确保机器人能够在不同方向的情况下顺利完成任务。 - 在main.py中整合新的任务调用，确保任务执行流程的连贯性和准确性。
299 lines
11 KiB
Python
299 lines
11 KiB
Python
import time
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import sys
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import os
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import math
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import threading
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import cv2
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import queue
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from threading import Thread, Lock
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from base_move.go_to_xy import go_to_xy
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from base_move.turn_degree import turn_degree, turn_degree_twice, turn_degree_v2
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from utils.log_helper import LogHelper, get_logger, section, info, debug, warning, error, success, timing
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from utils.decode_arrow import detect_arrow_direction, visualize_arrow_detection
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from base_move.move_base_hori_line import (
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arc_turn_around_hori_line,
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go_straight_by_hori_line,
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move_to_hori_line,
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align_to_horizontal_line
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)
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# 创建本模块特定的日志记录器
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logger = get_logger("任务2-5")
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observe = True
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# 异步箭头检测器类
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class AsyncArrowDetector:
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def __init__(self, image_processor):
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"""
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初始化异步箭头检测器
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参数:
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image_processor: ImageProcessor实例
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"""
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self.image_processor = image_processor
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self.detection_thread = None
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self.running = False
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self.lock = Lock()
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self.arrow_result = None
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self.result_time = 0
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self.last_processed_image = None
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# 用于保存可视化结果
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self.save_dir = "logs/image"
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os.makedirs(self.save_dir, exist_ok=True)
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info("异步箭头检测器已初始化", "初始化")
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def start_detection(self, interval=0.5):
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"""
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启动异步箭头检测
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参数:
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interval: 检测间隔，单位秒
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"""
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if self.detection_thread is not None and self.detection_thread.is_alive():
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info("异步箭头检测已经在运行中", "警告")
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return
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self.running = True
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self.detection_thread = Thread(target=self._detection_worker, args=(interval,))
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self.detection_thread.daemon = True
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self.detection_thread.start()
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info("启动异步箭头检测线程", "启动")
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def stop_detection(self):
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"""停止异步箭头检测"""
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self.running = False
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if self.detection_thread and self.detection_thread.is_alive():
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self.detection_thread.join(timeout=1.0)
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info("异步箭头检测线程已停止", "停止")
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def _detection_worker(self, interval):
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"""异步箭头检测工作线程"""
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last_detection_time = 0
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while self.running:
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current_time = time.time()
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# 按指定间隔检测
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if current_time - last_detection_time >= interval:
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img = self.image_processor.get_current_image()
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if img is not None:
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try:
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# 保存最后处理的图像
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self.last_processed_image = img.copy()
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# 检测箭头方向
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direction = detect_arrow_direction(img)
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with self.lock:
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self.arrow_result = direction
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self.result_time = current_time
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if direction != "unknown":
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info(f"异步检测到{direction}箭头", "箭头检测")
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# 保存检测结果的可视化图像
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timestamp = time.strftime("%Y%m%d_%H%M%S")
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save_path = f"{self.save_dir}/arrow_detection_{timestamp}.jpg"
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visualize_arrow_detection(img, save_path=save_path)
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info(f"箭头检测可视化结果已保存至: {save_path}", "箭头检测")
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except Exception as e:
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error(f"异步箭头检测出错: {str(e)}", "错误")
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last_detection_time = current_time
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# 短暂休眠避免占用过多CPU
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time.sleep(0.05)
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def get_last_result(self):
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"""获取最后一次成功的箭头检测结果"""
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with self.lock:
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return self.arrow_result, self.result_time, self.last_processed_image
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def run_task_2(ctrl, msg):
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# 微调 xy 和角度
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go_to_xy(ctrl, msg, 0.9, 0.25, speed=0.5, observe=True)
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turn_degree(ctrl, msg, 0.8, absolute=True)
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print('角度为',ctrl.odo_msg.rpy[2])
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#获取微调角度
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text=["直线走一段","第一个圆弧","微调路径","第二个圆弧","微调路径","第三个圆弧","微调路径","第四个圆弧","绕出来","前走一点"]
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# 连续三重弯道行走
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directions = [
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#直线走一段
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(0.4,0,0,0,0,0,1.2),
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#第一个圆弧
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(0.45, 0, 0.77,0,0,0,6.5),
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#微调路径
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(0.3,0,0,0,0,0,0.4),
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#第二个圆弧
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(0.4,0,-0.73,0,0,0,7.9),
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#微调路径
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(0.3,0,0,0,0,0,1),
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# 第三个圆弧
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(0.4,0,0.73,0,0,0,6.4),
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#微调路径
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(0.3,0,0,0,0,0,1.3),
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#第四个圆弧
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(0.4,0,-0.72,0,0,0,3.6),
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#绕出来
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(0.3,0,0.6,0,0,0,1),
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# #前走一点
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# (0.3,0,0,0,0,0,0.5)
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] # [vel_x, vel_z] 对应 [左转, 右转, 左转]
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gotoxy=[
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(0.87,0.23),
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(1.19,0.22),
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(0.91,1.55),
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(0.81,1.46),
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(0.67,2.59),
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(0.92,2.43),
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(1.53,3.62),
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(1.15,3.70),
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(0.63,4.73),
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]
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arrow_direction = None
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# 创建异步箭头检测器
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arrow_detector = AsyncArrowDetector(ctrl.image_processor)
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# 在进入第四个圆弧前（索引为7）启动异步箭头检测
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arrow_detection_started = False
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for i, (vel_x, vel_y, vel_z ,rpy_x,rpy_y,rpy_z,t) in enumerate(directions):
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# 在第四个圆弧开始前启动异步箭头检测
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if i == 7 and not arrow_detection_started:
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info("即将进入第四个圆弧，启动异步箭头检测", "箭头检测")
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arrow_detector.start_detection(interval=0.3)
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arrow_detection_started = True
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# 设置转向命令
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msg.mode = 11 # Locomotion
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msg.gait_id = 26 # TROT_FAST
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msg.vel_des = [vel_x, vel_y, vel_z] # [x, y, z]，y=0表示不侧移
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msg.rpy_des = [rpy_x, rpy_y, rpy_z]
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msg.duration = 0 # 连续运动
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msg.step_height = [0.03, 0.03]
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msg.life_count += 1
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ctrl.Send_cmd(msg)
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# 根据转弯方向调整持续时间（假设半圆需要3秒）
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go_to_xy(ctrl, msg, gotoxy[i][0], gotoxy[i][1], speed=0.5, observe=True)
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# 打印当前方向
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print(f"开始 {text[i]} ")
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print(f"第{i}次",'角度为',ctrl.odo_msg.rpy[2])
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print(f"第{i}次",'x为',ctrl.odo_msg.xyz[0])
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print(f"第{i}次",'y为',ctrl.odo_msg.xyz[1])
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print(f"第{i}次",'z为',ctrl.odo_msg.xyz[2])
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time.sleep(t) # 持续3秒
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# 在第四个圆弧完成后（索引为7）获取箭头检测结果
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if i == 7: # 最后一个弯道结束后
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info("完成第四个圆弧，开始检测箭头方向", "箭头检测")
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# 给异步检测一些时间来完成
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wait_time = 0
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max_wait = 2.0 # 最多等待2秒
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while wait_time < max_wait:
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# 获取异步检测结果
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result, result_time, last_image = arrow_detector.get_last_result()
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if result is not None and result != "unknown":
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arrow_direction = result
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info(f"成功检测到箭头方向: {arrow_direction}", "箭头检测")
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break
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time.sleep(0.1)
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wait_time += 0.1
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# 如果未检测到或结果为unknown，尝试在当前图像上再次检测
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if arrow_direction is None or arrow_direction == "unknown":
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info("异步检测未得到确定结果，尝试在当前图像上直接检测", "箭头检测")
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# 获取当前图像
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image = ctrl.image_processor.get_current_image()
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if image is not None:
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# 直接在当前图像上检测
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arrow_direction = detect_arrow_direction(image, observe=True)
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info(f"直接检测到箭头方向: {arrow_direction}", "箭头检测")
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# 保存检测结果的可视化图像
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timestamp = time.strftime("%Y%m%d_%H%M%S")
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save_path = f"logs/image/arrow_detection_final_{timestamp}.jpg"
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os.makedirs(os.path.dirname(save_path), exist_ok=True)
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visualize_arrow_detection(image, save_path=save_path)
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info(f"最终箭头检测可视化结果已保存至: {save_path}", "箭头检测")
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else:
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warning("无法获取当前图像，箭头方向检测失败", "箭头检测")
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arrow_direction = "unknown"
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# 停止异步箭头检测
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if arrow_detection_started:
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arrow_detector.stop_detection()
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print('角度为',ctrl.odo_msg.rpy[2])
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print('x为',ctrl.odo_msg.xyz[0])
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print('y为',ctrl.odo_msg.xyz[1])
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print('z为',ctrl.odo_msg.xyz[2])
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# 返回检测到的箭头方向
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return arrow_direction
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def run_task_2_back(ctrl, msg):
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# go_to_xy(ctrl, msg, 0.2, 1, speed=0.5, observe=True)
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go_to_xy(ctrl, msg, 0.7, 5, speed=0.5, observe=True)
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turn_degree_v2(ctrl, msg, -106.5, absolute=True)
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print('角度为',ctrl.odo_msg.rpy[2])
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print('x为',ctrl.odo_msg.xyz[0])
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print('y为',ctrl.odo_msg.xyz[1])
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print('z为',ctrl.odo_msg.xyz[2])
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text=["直线走一段","第一个圆弧","微调路径","第二个圆弧","微调路径","第三个圆弧","微调路径","第四个圆弧","绕出来","前走一点"]
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# 连续三重弯道行走
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directions = [
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(0.3,0,0,0,0,0,0.6),
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#第四个圆弧
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(0.4,0,0.69,0,0,0,3),
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#微调路径
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(0.3,0,0,0,0,0,1.3),
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# 第三个圆弧
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(0.4,0,-0.73,0,0,0,6),
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#微调路径
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(0.3,0,0,0,0,0,1.4),
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#第二个圆弧
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(0.4,0,0.74,0,0,0,7.4),
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#微调路径
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(0.3,0,0,0,0,0,1.2),
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#第一个圆弧
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(0.45, 0, -0.78,0,0,0,5.8),
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#直线走一段
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(0.4,0.05,0,0,0,0,0.3),
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(0.4,0,0,0,0,0,1.5),
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] # [vel_x, vel_z] 对应 [左转, 右转, 左转]
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for i, (vel_x, vel_y, vel_z ,rpy_x,rpy_y,rpy_z,t) in enumerate(directions):
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# 设置转向命令
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msg.mode = 11 # Locomotion
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msg.gait_id = 26 # TROT_FAST
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msg.vel_des = [vel_x, vel_y, vel_z] # [x, y, z]，y=0表示不侧移
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msg.rpy_des = [rpy_x, rpy_y, rpy_z]
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msg.duration = 0 # 连续运动
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msg.step_height = [0.03, 0.03]
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msg.life_count += 1
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ctrl.Send_cmd(msg)
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# 打印当前方向
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print(f"开始 {text[i]} ")
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# 根据转弯方向调整持续时间（假设半圆需要3秒）
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time.sleep(t) # 持续3秒 |