Session: 02-03-02: Optimization

Paper Number: 145298

145298 - Automatic Tool Alignment of an Eye-in-Hand Manipulator for Overhead Line Insulation Cleaning. 

Insulator cleaning plays a pivotal role in maintaining the integrity and efficiency of power transmission and distribution systems, directly influencing the reliability of electricity distribution. Over time, contaminants such as dust, pollution, and debris accumulate on insulator surfaces, compromising their insulating properties and increasing the risk of electrical failures and outages. Manual cleaning of the insulators poses significant safety challenges to the workers for maintaining the overhead lines. In response to these challenges, teleoperated robotic arms have emerged as a promising solution for insulator cleaning tasks, offering improved efficiency and safety compared to manual methods. However, the performance of teleoperated arms is inherently sensitive to the initial configurations of the arm, often requiring manual adjustment to ensure proper alignment with the target insulator. This manual configuration process can be time-consuming and error-prone, hindering the overall effectiveness of the cleaning operation.

 

Considering these limitations, this paper proposes a novel robotic system equipped with a manipulator featuring an "eye-in-hand" depth camera for insulator cleaning tasks. The key innovation of this system lies in its ability to autonomously align the end effector of the manipulator with optimal configurations, based on the pose of the target insulator as well as the current configuration of the manipulator, thereby eliminating the need for manual configuration and enhancing the efficiency and reliability of the cleaning process. By leveraging image processing and machine learning algorithms to interpret RGBD (Red, Green, Blue, Depth) data from the depth camera, it can estimate the position and orientation of the insulator in real-time, enabling the robotic system to adapt dynamically to the pose of the target insulator. 

Upon successful alignment, the robotic system can seamlessly transition to a teleoperation mode, allowing a human operator to fine-tune the cleaning process with precision control. This dual-mode operation combines the benefits of automation in handling repetitive alignment tasks with the nuanced control of human operators, ensuring thorough cleaning while minimizing the risk of damage to insulator surfaces. Moreover, by reducing the reliance on manual intervention, the proposed robotic system enhances worker safety and productivity in high-risk environments such as transmission line corridors and substations.

 

To validate the effectiveness and reliability of the proposed system, extensive experimental trials were conducted across different lighting conditions and pose of the target insulators with varying initial configurations of the system. The system was consistently able to align with respect to the pose of the insulator and clean it successfully.  

In conclusion, the development of this robotic manipulator system with an "eye-in-hand" depth camera represents a significant leap forward in the field of power transmission maintenance. By leveraging autonomous alignment and haptic teleoperation, this system offers a safer, more efficient, and effective solution for insulator cleaning, promising to set a new standard in the maintenance practices of the power transmission industry.

Presenting Author: Thani Althani Dubai Electricity & Water Authority

Presenting Author Biography: Thani Althani completed his Bachelors in Mechanical Engineering from the American University of Sharjah (AUS) in 2019. He joined DEWA’s R&D Center as an R&D Technologist working on robotics and drones research. Thani contributed to an autonomous desert terrain rover for ground albedo data collection. His main research interests are robot manipulation, dynamics and control, and unmanned aerial systems. Thani is currently pursuing his Masters in Electrical Engineering with a focus on robotics and controls at Rochester Institute of Technology (RIT) Dubai.

Authors:

Mohit Vohra Dubai Electricity & Water Authority
Amruta Panda Dubai Electricity & Water Authority
Prashanth Subramaniam Dubai Electricity & Water Authority
Thani Althani Dubai Electricity & Water Authority
Mahmoud Rezk Dubai Electricity & Water Authority