Computer-vision integrated robotic arm for autonomous space operations
- Paper ID
98060
- DOI
- author
- company
Vellore Institute of Technology; Indian Institute of Technology Kharagpur; Universidad Nacional Mayor de San Marcos
- country
India
- year
2025
- abstract
\documentclass[a4paper,10pt]{article} \usepackage{geometry} \geometry{margin=1in} \usepackage{amsmath} \begin{document} \title{\textbf{Computer Vision-Integrated Robotic Arms for Autonomous Space Operations}} \author{} \date{} \maketitle \begin{abstract} The integration of Computer Vision (CV) into robotic arms is transforming human-robot partnerships in space exploration by enabling autonomous operations in complex and dynamic environments. This research presents a CV-based robotic arm system designed for room assignments, utilizing deep learning algorithms for real-time object detection, precise manipulation, and adaptive functionality in microgravity. The system employs simultaneous localization and mapping (SLAM) to enhance spatial awareness, allowing the robotic arm to identify, track, and interact with mission-critical elements such as equipment, payloads, and spacecraft components. Additionally, a Bayesian decision network optimizes task execution under uncertain conditions, enabling real-time adjustments to operational constraints such as lighting variations, motion disturbances, and unexpected environmental changes. A key feature of the system is its human-in-the-loop architecture, where astronauts can supervise or override autonomous functions via an augmented reality interface. This enhances extravehicular activities (EVAs), docking operations, and orbital repairs while reducing astronaut workload and mission risks. Experimental results from simulated microgravity environments demonstrate a 50\% reduction in human intervention and a 40\% improvement in task completion compared to traditional teleoperated robotic systems. These advancements mark a critical step toward scalable autonomous infrastructure assembly, planetary surface operations, and deep-space habitat construction, reinforcing long-term human-robot collaboration in future space missions. \end{abstract} \end{document}