Integrating Advanced Sensor Fusion with User-Centered Design and Rapid Prototyping in Robotics: A Comprehensive Review
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Integrating Advanced Sensor Fusion with User-Centered Design and Rapid Prototyping in Robotics: A Comprehensive Review
Parth Chandak
parth.chandak02@gmail.com
Abstract
This systematic review examines the evolution and current state of sensor fusion approaches in robotics from 2004 to 2023 by analyzing 15 selected papers in the field. The review surveys both theoretical foundations and practical implementations, documenting the progression from traditional probabilistic methods to contemporary deep learning approaches. Based on the analyzed papers, several trends could be observed: a development from two sensor integration to multi-modal architectures, the introduction of end-to-end learning approaches that combine feature extraction and fusion processes, and research into user-centered design and rapid prototyping for practical applications. The reviewed papers discuss various approaches, including deep learning methods for multi-modal perception and real time sensor calibration, as well as hybrid approaches that combine neural networks with probabilisticmethods. The examined literature identifies numerous ongoing challenges, including standardization of evaluation metrics, sensor uncertainty handling, and real-time processing architectures. This review summarizes the capabilities and limitations discussed in the reviewed papers regarding sensor fusion in robotics while highlighting the various research directions proposed by authors in this field.
Keywords
Sensor Fusion, Robotics, User-Centered Design, Rapid Prototyping, Deep Learning, Multi-Modal Perception, System Integration, Real-time Processing