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Integrating Advanced Sensor Fusion with User-Centered Design and Rapid Prototyping in Robotics: A Comprehensive Review

Authors:

Parth Chandak

parth.chandak02@gmail.com

Abstract                                                                                                       

The integration of multi-modal sensor fusion with user-centered design principles and rapid prototyping methodologies has emerged as a transformative approach in modern robotics. This systematic review analyzes the evolution and current state of sensor fusion approaches in robotics from 2004 to 2023, examining 15 seminal papers that have shaped the field’s development. Through careful analysis of both theoretical foundations and practical implementations, we trace the progression from traditional probabilistic methods to contemporary deep learning approaches. Our review reveals three major trends that have shaped the field: the transition from simple two-sensor integration to sophisticated multi-modal architectures, the emergence of end-to-end learning approaches that unify feature extraction and fusion processes, and the growing emphasis on user-centered design and rapid prototyping in real-world applications. While deep learning methods have advanced the state-of-the-art in tasks such as multi-modal perception and real-time sensor calibration, our analysis reveals that hybrid approaches—which combine data-driven neural networks with traditional probabilistic methods—achieve superior robustness and reliability. These hybrid systems particularly excel when integrated with user-centered design principles, offering both high performance and practical usability. We identify several critical challenges, including the need for standardized evaluation metrics, improved handling of sensor uncertainty, and more efficient real-time processing architectures that can be rapidly prototyped and deployed. This review provides a comprehensive framework for understanding the current capabilities and limitations of sensor fusion in robotics while offering insights into future research directions that emphasize both technical advancement and practical usability.

Keywords:

Sensor Fusion, Robotics, User-Centered Design, Rapid Prototyping, Deep Learning, Multi-Modal Perception, System Integration, Real-time Processing