Sensor Guided Docking of Autonomous Mobile Robot for Battery Recharging

Rao*, M V Sreenivas; Shivakumar, M

doi:10.35940/ijrte.d8176.118419

Cited by 6 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The effectiveness of the developed approach was demonstrated through experiments. In [17], ultrasonic sensors and IR sensors were implemented for autonomous docking and recharging of a wheeled mobile robot. In the proposed approach, ultrasonic sensors were utilized to detect the charging station and estimate distance from it and IR sensor were employed to tune the orientation of the mobile robot at the exact position for docking purpose.…”

Section: A Autonomous Docking and Recharging Of Mobile Robot Systemsmentioning

confidence: 99%

A Laser Intensity Based Autonomous Docking Approach for Mobile Robot Recharging in Unstructured Environments

Liu

2022

IEEE Access

View full text Add to dashboard Cite

Autonomous recharging is a fundamental requirement for autonomous mobile robots in order to allow them to work continuously without human intervention, and autonomous docking to a charging station is a challenging yet promising research area. In particular, the docking task becomes even more complicated in unstructured human environments when the charging station's location is not fixed and when there are dynamic obstacles moving around. This paper presents a laser intensity based autonomous docking approach, which allows a mobile robot to recharge its battery autonomously in unstructured environments. Laser reflection intensity for a self-adhesive reflective tape is quantitatively investigated, and the sufficient/necessary conditions for successful reflector detection are discussed. Using the proposed reflector detection technique, the charging station can be easily distinguished from similar objects in an unstructured environment. Comparing to the traditional docking methods, the developed approach is easier to implement and can significantly improve the reliability of autonomous docking and recharging. Extensive experiments were conducted to verify the effectiveness of the developed autonomous docking approach.

show abstract

Section: A Autonomous Docking and Recharging Of Mobile Robot Systemsmentioning

confidence: 99%

A Laser Intensity Based Autonomous Docking Approach for Mobile Robot Recharging in Unstructured Environments

Liu

2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The unmanned vehicle determines whether it needs to be charged and starts charging back autonomously when the power is low. There are various ways to dock unmanned vehicles for autonomous charging [1], and most existing small robots rely on machine vision, laser, infrared and other methods to guide the robot charging plug to dock with the charging stand to complete autonomous charging. Most unmanned vehicle charging solutions apply the method Fig.…”

Section: Introductionmentioning

confidence: 99%

Autonomous charging docking control method for unmanned vehicles based on vision and infrared

Zhou,

He,

Yan

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Unmanned vehicle charging is part of the autonomous workflow of unmanned vehicles. Most existing unmanned vehicles mostly rely on manual battery change or manual charging, which cannot realize autonomous charging. In order to achieve simpler and safer autonomous charging for unmanned vehicles, this paper proposes a new intelligent unmanned vehicle autonomous charging docking method based on infrared guidance and vision assistance. Firstly, the autonomous charging device and intelligent charging stand for unmanned vehicles are designed, and for the unmanned vehicle, charging is not easy to align and easy to detach when charging. The camber-type electric core and charging adsorption device are designed, respectively, and the autonomous charging docking device is designed. Secondly, in order to ensure the accuracy of the docking between the unmanned vehicle and the intelligent charging stand, the unmanned vehicle autonomous charging method is proposed. The combination method of infrared and vision adjusts the posture of the unmanned vehicle. Finally, a protection method of autonomous charging docking based on ultrasonic ranging of unmanned vehicles is proposed. The communication and ranging modules on the unmanned vehicle and intelligent charging stand are designed to prevent mistouching and obstacle avoidance to ensure the safety of the system. The experiment results show that the docking method of this unmanned vehicle autonomous charging system is accurate, efficient, and safe, which can satisfy the demand for unmanned vehicle autonomous charging.

show abstract

“…To overcome the challenges of conventional methods, the combination of different sensors has been investigated for years, and recent research has proven that the fusion approach yields better performance than a single-sensor method [14]; the limitations of IR-based, laser-based, and vision-based methods for autonomous docking and recharging are overcome by combining multiple sensors. The authors of [15] attempted to integrate a camera and IR sensor with laser range finders in order to improve the reliability of the autonomous docking process. In [16], a vision-based autonomous docking and recharging approach was applied to a security robot.…”

Section: Introductionmentioning

confidence: 99%

Vision- and Lidar-Based Autonomous Docking and Recharging of a Mobile Robot for Machine Tending in Autonomous Manufacturing Environments

Jia,

Afaq,

Ripka

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

Autonomous docking and recharging are among the critical tasks for autonomous mobile robots that work continuously in manufacturing environments. This requires robots to demonstrate the following abilities: (i) detecting the charging station, typically in an unstructured environment and (ii) autonomously docking to the charging station. However, the existing research, such as that on infrared range (IR) sensor-based, vision-based, and laser-based methods, identifies many difficulties and challenges, including lighting conditions, severe weather, and the need for time-consuming computation. With the development of deep learning techniques, real-time object detection methods have been widely applied in the manufacturing field for the recognition and localization of target objects. Nevertheless, those methods require a large amount of proper and high-quality data to achieve a good performance. In this study, a Hikvision camera was used to collect data from a charging station in a manufacturing environment; then, a dataset for the wireless charger was built. In addition, the authors of this paper propose an autonomous docking and recharging method based on the deep learning model and the Lidar sensor for a mobile robot operating in a manufacturing environment. In the proposed method, a YOLOv7-based object detection method was developed, trained, and evaluated to enable the robot to quickly and accurately recognize the charging station. Mobile robots can achieve autonomous docking to the charging station using the proposed Lidar-based approach. Compared to other methods, the proposed method has the potential to improve recognition accuracy and efficiency and reduce the computation costs for the mobile robot system in various manufacturing environments. The developed method was tested in real-world scenarios and achieved an average accuracy of 95% in recognizing the target charging station. This vision-based charger detection method, if fused with the proposed Lidar-based docking method, can improve the overall accuracy of the docking alignment process.

show abstract

Sensor Guided Docking of Autonomous Mobile Robot for Battery Recharging

Cited by 6 publications

References 8 publications

A Laser Intensity Based Autonomous Docking Approach for Mobile Robot Recharging in Unstructured Environments

A Laser Intensity Based Autonomous Docking Approach for Mobile Robot Recharging in Unstructured Environments

Autonomous charging docking control method for unmanned vehicles based on vision and infrared

Vision- and Lidar-Based Autonomous Docking and Recharging of a Mobile Robot for Machine Tending in Autonomous Manufacturing Environments

Contact Info

Product

Resources

About