The rapid expansion of robotic systems in real-world applications has been fundamentally enabled by significant advancements in sensing technologies. This technical review explores the multifaceted sensing ecosystem required for contemporary robotic platforms to effectively perceive, navigate, and interact with complex environments. Beyond controlled laboratory settings, real-world deployment necessitates sophisticated multimodal sensing architectures that process diverse environmental inputs simultaneously, adapt to unpredictable changes, and make decisions with minimal latency. The article examines current state-of-the-art implementations across visual, ranging, and positional sensing modalities, exploring how these systems integrate through complementary, redundant, and cooperative fusion methodologies. Additionally, the review covers motion and proprioceptive sensing through inertial measurement units and advanced feedback systems that enable precise control. Real-time processing challenges and solutions are discussed, including edge computing paradigms and machine learning approaches for sensor fusion. Finally, emerging directions in miniaturization, neuromorphic sensing, and integrated sensor-actuator systems are evaluated, highlighting how these technological frontiers will shape next-generation robotic capabilities.
Keywords: edge computing, integrated sensor-actuator systems, multimodal sensor fusion, neuromorphic sensing, robotic perception
