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Design and fabrication of an augmented reality-enabled, AI-assisted autonomous mobile robot with dual six-axis robotic arms for advanced object manipulation
Thesis   Open access

Design and fabrication of an augmented reality-enabled, AI-assisted autonomous mobile robot with dual six-axis robotic arms for advanced object manipulation

Nijanthan Vasudevan
Master of Science (M.S.), Drexel University
Dec 2023
DOI:
https://doi.org/10.17918/00001743
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Abstract

Artificial intelligence Mecanum wheel Mobile robots Object manipulation Augmented Reality Robotics
This thesis presents the design and fabrication of an autonomous mobile robot with dual six-axis robotic arms, enhanced by augmented reality (AR) and powered by artificial intelligence (AI). The innovation aims to advance object manipulation tasks in various complex and dynamic environments, potentially for industrial applications. The system's Artificial Intelligence feature enhances the robot's ability to navigate and interact with its surroundings more accurately. The AR interface also allows human operators to intuitively control and guide the robot's actions in real time when needed, bridging the gap between autonomous operation and human oversight. The dual six-axis robotic arms enable dexterous and precise object manipulation. These arms mimic the versatility and adaptability of human arms, opening new possibilities for tasks that were previously challenging for traditional robotic systems. In developing this advanced mobile robot, this work embodies a pioneering step in autonomous robotics, showcasing a blend of AI, AR, and mechanical design. The robot's capabilities in object manipulation present a leap forward in robotics, promising a future where robots can take on more complex roles in our societies, while also offering a practical solution to labor-intensive or high-risk tasks. The research concludes with extensive testing and validation of the robot, demonstrating its effectiveness and efficiency in performing complex object manipulation tasks autonomously in various controlled and real-world scenarios. The results suggest promising implications for the future of robotics and automation, reinforcing the importance of interdisciplinary approaches in technological advancement.

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