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Depth Perception and Spatial Vision01:15

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Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
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Monocular Robust Depth Estimation Vision System for Robotic Tasks Interventions in Metallic Targets.

Carlos Veiga Almagro1, Mario Di Castro2,3, Giacomo Lunghi2,4

  • 1CERN, EN-SMM Survey, Measurement and Mechatronics group, 1217 Geneva, Switzerland. carlos.veiga.almagro@cern.ch.

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Summary

This study introduces a new vision system for robotic interventions, enhancing safety and efficiency in hazardous environments. The system accurately tracks metallic targets, reducing operator fatigue and improving mission performance.

Keywords:
eye-in-handhazardous environmentshuman-supervisory controlradioactive scenariosrobotic interventionsteleroboticstrackingvision

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Area of Science:

  • Robotics
  • Computer Vision
  • Human-Robot Interaction

Background:

  • Robotic interventions in hazardous environments require high safety standards and often expert operator involvement.
  • Multi-modal Human-Robot Interfaces (HRIs) enable manual control and semi-autonomous behaviors, improving interaction in critical and secure scenarios.
  • Challenges include maintaining visibility and handling partial occlusions during robotic operations.

Purpose of the Study:

  • To develop and validate a novel vision system for tracking and estimating the depth of metallic targets for robotic interventions.
  • To enhance the safety and efficiency of robotic operations in hazardous scenarios.
  • To reduce operator cognitive load and stress during complex or repetitive tasks.

Main Methods:

  • A novel vision system utilizing on-hand monocular cameras was designed.
  • The system focuses on solving issues of lack of visibility and partial occlusions.
  • Object tracking and recognition techniques were employed for semi-autonomous behaviors.

Main Results:

  • The vision system achieved 95% success in autonomous mode and 100% in supervised mode during real interventions at CERN.
  • The system demonstrated effectiveness in tracking and estimating depth of metallic targets.
  • Validated in real-world applications at the Centre for Nuclear Research (CERN) accelerator facilities.

Conclusions:

  • The developed vision system significantly increases the safety and efficiency of robotic operations.
  • It effectively reduces operator cognitive fatigue and stress, particularly during non-critical or repetitive mission phases.
  • Integration of such assistance systems is crucial for enhancing performance and safety in complex robotic tasks.