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Perception

Perception

Perception is a fundamental psychological process that enables individuals to organize, interpret, and consciously experience sensory information. This process is crucial for understanding and interacting with the world around us. It includes both bottom-up and top-down processing, each playing a distinct role in how we perceive our environment.
Bottom-up processing begins at the sensory level, where receptors detect external environmental stimuli. These could include the tactile sensation of...

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Related Experiment Video

Updated: Sep 7, 2025

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

Published on: June 7, 2024

Terrain Perception Using Wearable Parrot-Inspired Companion Robot, KiliRo.

Jaishankar Bharatharaj^1,2, Loulin Huang³, Ahmed M Al-Jumaily¹

¹Institute of Biomedical Technologies, Auckland University of Technology, Auckland 1010, New Zealand.

Biomimetics (Basel, Switzerland)

|June 23, 2022

Summary

This summary is machine-generated.

This study developed a wearable robot system, KiliRo, to prevent falls by classifying terrain changes. The system achieved over 95% accuracy in identifying five different ground types, enhancing walking safety.

Keywords:

KiliRo parrot inspired robot terrain perception wearable robot

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Last Updated: Sep 7, 2025

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Area of Science:

Robotics
Computer Vision
Human-Computer Interaction

Background:

Falls are a leading cause of unintentional injury deaths globally.
Increased risk factors include mobile phone use, impaired vision, and unexpected terrain changes.
A proactive warning system is needed to mitigate fall-related injuries.

Purpose of the Study:

To develop and validate a terrain perception system for a wearable robot.
To alert users to imminent terrain changes and potential fall hazards.
To enhance safety for individuals prone to falls.

Main Methods:

Utilized a bio-inspired wearable robot, KiliRo, with a 180-degree camera range.
Employed image processing for visual feature extraction from captured terrain images.
Implemented K-nearest neighbor algorithm for terrain classification.

Main Results:

The terrain perception system achieved over 95% accuracy.
Successfully classified five distinct terrain types: pedestrian pathway, road, grass, interior, and staircase.
Demonstrated the efficacy of the visual-based approach for real-time terrain analysis.

Conclusions:

The KiliRo robot's terrain perception system effectively identifies diverse terrain types.
This technology offers a promising solution for fall prevention by warning users of hazards.
The system's high accuracy supports its potential for real-world application in enhancing mobility safety.