自主移动机器人按下电梯按钮的混合导航

Pan-Long Wu, Zhe-Ming Zhang, Chuin Jiat Liew, Jinsiang Shaw
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引用次数: 0

摘要

提出了一种具有眼-手机械臂的自主移动机器人(AMR)。AMR可以使用ORB-SLAM算法(面向FAST(来自加速片段测试的特征)和旋转BRIEF(二进制鲁棒独立基本特征)特征检测器-同时定位和映射)构建地图并进行定位。它还能够利用2d激光雷达传感器的信息实时避障。AMR、机械手、摄像头、传感器等都集成在机器人操作系统(ROS)下。在按动电梯按钮调度AMR的实验研究中,将实验室启动的AMR导航分为三个部分。首先,AMR在大部分行程中使用ORB-SLAM启动导航,到达电梯附近的航路点。所得的平均绝对误差(MAE)在x轴上为8.5 cm,在y轴上为10.8 cm,绕z轴旋转9.2度,与参考点的线性位移为15.1 cm。接下来,ORB-SLAM被一种基于里程计的2D-SLAM方法所取代,以进一步将AMR从航路点导航到1.5至3米距离的面向电梯的点,在这种情况下,由于定位的特征点稀疏,ORB-SLAM是无效的,并且电梯可以被AMR上的手眼机器视觉清晰地检测到。最后,机器视觉识别电梯的空间位置,并再次使用基于里程计的二维SLAM方法将AMR导航到电梯前方0.3至0.5米的距离。只有在这个阶段,小尺寸的电梯按钮才能被AMR上的机械臂检测到并到达。实验结果表明,在实验室启动的AMR按下按钮的平均成功率为60%。并指出了电梯按钮成功压下率的改进措施。
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Hybrid Navigation of an Autonomous Mobile Robot to Depress an Elevator Button
The development of an autonomous mobile robot (AMR) with an eye-in-hand robot arm atop for depressing elevator button is proposed. The AMR can construct map and perform localization using the ORB-SLAM algorithm (the Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features) feature detector-Simultaneous Localization and Mapping). It is also capable of real-time obstacle avoidance using information from 2D-LiDAR sensors. The AMR, robot manipulator, cameras, and sensors are all integrated under robot operating system (ROS). In experimental investigation to dispatch the AMR for depressing an elevator button, AMR navigation initiating from the laboratory is divided into three parts. First, the AMR initiated navigation using ORB-SLAM for most of the journey to a waypoint nearby the elevator. The resulting mean absolute error (MAE) is 8.5 cm on the x-axis, 10.8 cm on the y-axis, 9.2-degree rotation angle about the z-axis, and the linear displacement from the reference point is 15.1 cm. Next, the ORB-SLAM is replaced by an odometry based 2D-SLAM method for further navigating the AMR from waypoint to a point facing the elevator between 1.5 to 3 meter distance, where the ORB-SLAM is ineffective due to sparse feature points for localization and where the elevator can be clearly detected by an eye-in-hand machine vision onboard the AMR. Finally, the machine vision identifies space position of the elevator and again the odometry based 2D SLAM method is employed for navigating the AMR to front of the elevator between 0.3 to 0.5 meter distance. Only at this stage, the small-size elevator button can be detected and reached by the robot arm on the AMR. An averaged 60% successful rate of button depressing by the AMR starting at the laboratory is obtained in the experiments. Improvements of successful elevator button depressing rate are also pointed out.
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来源期刊
Journal of Automation, Mobile Robotics and Intelligent Systems
Journal of Automation, Mobile Robotics and Intelligent Systems Engineering-Control and Systems Engineering
CiteScore
1.10
自引率
0.00%
发文量
25
期刊介绍: Fundamentals of automation and robotics Applied automatics Mobile robots control Distributed systems Navigation Mechatronics systems in robotics Sensors and actuators Data transmission Biomechatronics Mobile computing
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