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2 2022

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Hybrid navigation of an autonomous mobile robot to depress an elevator button

Wu Pan-Long, Zhang Zhe-Ming, Liew Chuin Jiat, Shaw Jin-Siang

Journal of Automation Mobile Robotics and Intelligent Systems

2022

Vol. 16, No. 4

25--35

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 maps 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 a robot operating system (ROS). In experimental investigation to dispatch the AMR to depress 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 the position in space of the elevator and again the odometry-based 2D-SLAM method is employed for navigating the AMR to the front of the elevator between 0.3 to 0.5 meter distance. Only at this stage can the small elevator button be detected and reached by the robot arm on the AMR. An average 60% successful rate of button depressing by the AMR starting at the laboratory is obtained in the experiments. Improvements for successful elevator button depressing rate are also pointed out.

Development of an omnidirectional AGV by applying ORB-SLAM for navigation under ROS framework

Wu Pan-Long, Li Jyun-Jhen, Shaw Jin-Siang

Journal of Automation Mobile Robotics and Intelligent Systems

2022

Vol. 16, No. 1

14--20

This paper presents the development of an automated guided vehicle with omni-wheels for autonomous navigation under a robot operating system framework. Specifically, a laser rangefinder-constructed two-dimensional environment map is integrated with a three-dimensional point cloud map to achieve real-time robot positioning, using the oriented features from accelerated segment testing and a rotated binary robust independent elementary feature detector-simultaneous localization and mapping algorithm. In the path planning for autonomous navigation of the omnidirectional mobile robot, we applied the A* global path search algorithm, which uses a heuristic function to estimate the robot position difference and searches for the best direction. Moreover, we employed the time-elastic-band method for local path planning, which merges the time interval of two locations to realize time optimization for dynamic obstacle avoidance. The experimental results verified the effectiveness of the applied algorithms for the omni-wheeled mobile robot. Furthermore, the results showed a superior performance over the adaptive Monte Carlo localization for robot localization and dynamic window approach for local path planning.