Obstacle Avoidance for Autonomous Mobile Robots based on Position Prediction using Fuzzy Inference
Obstacle Avoidance for Autonomous Mobile Robots based on Position Prediction using Fuzzy Inference
复制标题
基于模糊推理位置预测的自主移动机器人避障
DOI：
10.5772/24494
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Masaki Takahashi
中科院分区：
文献类型：
--
作者：
Takafumi Suzuki;Masaki Takahashi
在未来，不难想象，我们将经常遇到许多自主的移动的机器人穿越我们居住的人口稠密的地方。在这种情况下，由于自主移动的机器人需要在未知障碍物的环境中执行任务，因此避障是机器人的重要功能之一。为了实现在室内工作的自主移动的机器人，我们采用了如图1（左）所示的全向平台。为了进行实验验证，研制了一台全方位移动的机器人，如图1（右）所示。该机器人具有用于环境识别的全向摄像头，并可以通过四个全向轮向各个方向移动。虽然有很多避障方法的研究集中在回避的可能性，本文提出的方法不仅关注的可能性，而且更安全的避障轨迹。即使有相同的情况下，机器人需要避免一个静态的障碍物，开始回避行为的时机应该根据机器人的速度而变化。如果障碍物也在移动，则定时应根据障碍物的速度而变化。举一个例子，在如图2所示的机器人和障碍物彼此经过的情况下，机器人应该根据障碍物的速度和自己的速度，沿着曲线（iii）避开。为了使机器人在未知的环境中能够高效、安全地进行避障，需要根据障碍物当前的运动来预测未来障碍物的位置。介绍了一种引入障碍物相对于机器人速度的实时避障方法。通过考虑根据时间和相对速度计算的机器人和障碍物的预测位置，机器人可以根据障碍物和机器人的速度在适当的时间开始回避行为。一些研究关注障碍物的速度（Ko & Lee，1996）以有效地避开移动障碍物。在本研究中，虚拟距离函数定义的基础上，到障碍物的距离和障碍物的速度，但是，只考虑的单位向量上的投影障碍物的速度从障碍物到机器人。换句话说，不考虑机器人的速度。
In the future, it’s not difficult to image that we will often come across many autonomous mobile robots traversing densely populated place we live in. In such situation, because the autonomous mobile robots need to carry out their tasks in a place with unknown obstacles, the obstacle avoidance is one of the important functions of the robots. With a view to implementation of autonomous mobile robot working in doors, we employ an omnidirectional platform as shown in Fig. 1 (left). For experimental verification, an omnidirectional mobile robot shown in Fig. 1 (right) is developed. The robot has an omnidirectional camera for environmental recognition, and can move to all directions by four omni wheels. While there are many studies about obstacle avoidance method focusing attention on possibility of avoidance, this paper presents the method focusing on not only possibility but also safer trajectory of avoidance. Even if there are the same situations that the robot needs to avoid a static obstacle, timing of beginning avoidance behaviour should vary according to the robot speed. If the obstacles are moving also, the timing should vary according to the velocities of the obstacles. To cite a case, in a situation that a robot and an obstacle go by each other as shown in Fig. 2, the robot should avoid along the curved line like (iii) according to the speeds of the obstacle and own speed. In order to get to the goal with efficient and safe avoidance behaviour in the unknown environment for the robots, predicting the future obstacles’ positions by their current motions is needed. This paper introduces a real-time obstacle avoidance method introducing the velocity of obstacle relative to the robot. By means of considering predicted positions of the robot and the obstacle calculated from the time and the relative velocity, the robot can begin the avoidance behaviour at an appropriate time according to the velocity of the obstacle and the robot. Some researches focus attention on the velocity of obstacle (Ko & Lee, 1996) to avoid moving obstacles efficiently. In this research, virtual distance function is defined based on distance from the obstacle and speed of obstacle, however, only projection of the obstacle velocity on the unit vector from the obstacle to the robot is considered. In other words, the velocity of the robot is not considered.