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Related Concept Videos

Introduction to Special Senses01:26

Introduction to Special Senses

Sensory receptors play an integral part in comprehending our external and internal environments. They receive diverse stimuli, converting them into the nervous system's electrochemical signals. This conversion occurs as the stimulus alters the sensory neuron's cell membrane potential, instigating the generation of an action potential. This action potential is subsequently transmitted to the central nervous system (CNS), which integrates with other sensory data or higher cognitive functions.
Sensory Modalities01:15

Sensory Modalities

Sensation typically is the process by which the sensory receptors and sense organs detect stimuli from the internal and external environment and transmit this information to the central nervous system for processing.
General senses refer to the broad category of sensory information detected by receptors in the body and can be further grouped into somatic and visceral senses. Somatic sensations include touch, pressure, temperature, and pain and are essential for navigating our environment and...
Muscle Coordination and Action01:24

Muscle Coordination and Action

Muscle coordination is a complex and finely tuned process essential for smooth and purposeful movements like flexion, extension, adduction, abduction, and rotation. The human body orchestrates the actions of various muscles working in concert, each with a specific role. Four functional types describe how muscles work together: agonist, antagonist, synergist, and fixator.
Agonists
Agonist muscles, often called prime movers, are the primary muscles responsible for producing a specific movement.
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...

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Related Experiment Video

Updated: Jun 13, 2026

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

Sensing the Action: Rethinking Sensor Modalities and Multi-Modal Fusion in Vision-Language-Action Models for Robotic

Byoung Chul Ko1

  • 1Department of Computer Engineering, Keimyung University, Daegu 42601, Republic of Korea.

Sensors (Basel, Switzerland)
|June 12, 2026
PubMed
Summary
This summary is machine-generated.

This survey reinterprets Vision-Language-Action (VLA) models through a sensor-fusion-action lens, highlighting sensor modality selection and fusion for improved robotic manipulation. It calls for a sensor-centric approach to advance Physical AI.

Keywords:
Sensor–Fusion–ActionVision–Language–Actionaction representationevaluation protocolrobotic manipulationsensor fusion

Related Experiment Videos

Last Updated: Jun 13, 2026

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
05:21

Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

Published on: January 7, 2019

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Sensor Fusion

Background:

  • Vision-Language-Action (VLA) models integrate language, vision, and control for general-purpose robotic policies.
  • Existing research often overlooks sensor modality selection, fusion, and their impact on robotic manipulation.
  • Real-world robotic performance and safety are critically dependent on sensor data processing.

Purpose of the Study:

  • To address the gap in understanding sensor modalities within VLA models by adopting a sensor-fusion-action pipeline framework.
  • To systematically analyze sensor modalities, data collection, and fusion techniques for robotic manipulation.
  • To advocate for a sensor-centric evaluation framework for next-generation Physical AI.

Main Methods:

  • Systematic taxonomy and comparison of major sensor modalities (RGB, depth, tactile, force/torque, proprioception, IMU, multi-spectral/thermal, event-based vision).
  • Review of teleoperation, human video, and simulation-based data collection pipelines and datasets.
  • Analysis of multi-modal design space including fusion techniques (early, late, cross-attention, token-level) and action representations.

Main Results:

  • Identified key characteristics, failure modes, and deployment constraints for various sensor modalities.
  • Highlighted a bias in current benchmarks towards RGB-centric inputs and single performance metrics.
  • Revealed the importance of multi-modal sensor fusion for effective robotic action generation.

Conclusions:

  • A sensor-centric perspective is crucial for advancing VLA models beyond current limitations.
  • A multidimensional evaluation framework is needed, considering robustness, safety, latency, and efficiency.
  • This survey provides a foundation for developing more capable and reliable Physical AI systems.