Session: 03-15-02: Smart Manufacturing and Robotics for the Future II

Paper Number: 160139

A Camera-Based Teleoperation System for a Robot Manipulator With Gripper Haptic Feedback 

 The design and manufacturing of mechatronic systems are integral to advancing both educational tools and research capabilities, particularly in robotics. The use of advanced equipment and infrastructure in academic institutions allows students to develop abilities to perform complex laboratory activities, a challenge that underscores the growing need for accessible, low-cost technological solutions. To address this gap, this article presents the design, development, and validation of a mechatronic system for teleoperation, aimed at enhancing remote laboratory experiences. By combining mechanical design, electronic systems, and advanced control algorithms, the proposed teleoperation system serves as a versatile platform for education and research in robotics, with applications in teleoperation, control, and pose estimation.

The development of the system was guided by the V-Model methodology, a systematic approach frequently used in the design of mechatronic systems to ensure that all subsystems are rigorously validated before full system integration. Each phase of the design and manufacturing process emphasized modularity, cost-efficiency, and scalability. The teleoperation system includes a robotic manipulator, a haptic feedback device, and a camera-based pose estimation algorithm. The mechanical components of the system were designed for ease of fabrication, using widely available materials and modern manufacturing techniques, ensuring both functionality and accessibility.

Central to the operation of the system is the use of an ArUco-based pose estimation algorithm, which tracks the position of a haptic tool manipulated by the user. This data is used to control a UR3 robot manipulator in real-time, enabling precise manipulation tasks. The haptic device not only guides the robotic gripper but also provides force feedback to the user, allowing for a more immersive teleoperation experience. By integrating advanced control algorithms with real-time data processing, the system achieves high responsiveness and accuracy in performing remote tasks.

Validation of the system was conducted through a series of experiments involving participants performing remote pick-and-place tasks. The results demonstrated that users could successfully complete these tasks, with significant improvements in task completion times as they gained experience. These findings highlight the effectiveness of the system in providing an engaging and functional teleoperation experience, even for users with limited prior exposure to robotics. The integration of haptic feedback was found to be particularly beneficial, enhancing the user’s ability to perform precise and controlled manipulations.

The design and manufacturing process focused not only on technical performance but also on creating a platform that is adaptable to future enhancements. For instance, the modular architecture of the system allows for the integration of additional features, such as improved motion smoothness and enhanced pose estimation under dynamic conditions. These improvements are critical for expanding the system’s capabilities in both educational and research contexts.

Presenting Author: Sebastian Roa Prada Universidad Autónoma De Bucaramanga

Presenting Author Biography: Sebastián Roa Prada is a professor at the Department of Mechatronics Engineering of Universidad Autónoma de Bucaramanga, in Bucaramanga, Colombia.

Authors:

Diego A. Carvajal Solano Universidad Autonoma de Bucaramanga
Sebastian Roa Prada Universidad Autónoma De Bucaramanga
Oscar E. Rueda Sanchez Universidad Autónoma de Bucaramanga
Daniel A. Vargas Rivera Universidad Autónoma de Bucaramanga