论文标题
一组移动机器人在混乱区域跟踪入侵者的分散决策和导航策略
Decentralized decision making and navigation strategy for tracking intruders in a cluttered area by a group of mobile robots
论文作者
论文摘要
In the current era of the industrial revolution, mobile robots are playing a pivotal role in helping out mankind in many complex and hazardous environments for performing tasks like search and rescue, obstacle avoidance, mining and security surveillance, etc. A lot of navigation algorithms have been developed in recent years but novel challenges still exist in autonomous path planning of multiple robots to track and follow multiple intruders.该报告展示了一组移动机器人的基于算术平均导航算法的分散策略，以浏览一个未知的环境，这些环境充满了障碍，以检测和遵循多个入侵的入侵者。建议的导航策略可确保移动机器人在周围的障碍物中间安全地移动，以保持安全距离并避免与障碍物和彼此碰撞。常规的颜色识别方法用于检测动态入侵者并使用Microsoft Kinect传感器摄像机计算像素值。引入了危险算法的概率，以确保环境中存在的所有入侵者之后，在入侵者及其追随者之间的最小距离的基础上都有友好的机器人。移动机器人遵循其像素值碱基上的入侵者运动。低像素值意味着入侵者很远，高像素值表示入侵者更接近友好的机器人。所有算法和图像处理技术均在Webots模拟环境中使用C编程语言实现和测试，结果表明，在算法之后，提出的基于算术平均值的导航和基于危险的入侵者的概率的成功。
In the current era of the industrial revolution, mobile robots are playing a pivotal role in helping out mankind in many complex and hazardous environments for performing tasks like search and rescue, obstacle avoidance, mining and security surveillance, etc. A lot of navigation algorithms have been developed in recent years but novel challenges still exist in autonomous path planning of multiple robots to track and follow multiple intruders. This report demonstrates a decentralized strategy of arithmetic mean based navigation algorithm for a group of mobile robots to navigate through an unknown environment filled with obstacles to detect and follow multiple invading intruders. The suggested navigation strategy ensures that mobile robots safely move right in the middle of surrounding obstacles to maintain a safe distance and to avoid collision with obstacles and each other. The conventional method of color recognition is used to detect dynamic intruders and calculate pixel values using the Microsoft Kinect sensor camera. A probability of danger algorithm is introduced to ensure that all the intruders present in the environment are being followed by friendly robots on the bases of the minimum distance between an intruder and its follower. The mobile robots follow intruders movement on the bases of their pixel values. The low pixel value means that intruder is far away and high pixel value represents that intruder is closer to the friendly robots. All the algorithms and image processing techniques are implemented and tested in WEBOTS simulation environment using C programming language and the results show the success of proposed arithmetic mean based navigation and probability of danger based intruders following algorithms.
