Search research articles

Related Concept Videos

Multi-input and Multi-variable systems

Multi-input and Multi-variable systems

Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Model-Free Transformer Framework for 6-DoF Pose Estimation of Textureless Tableware Objects.

Sensors (Basel, Switzerland)·2025

Same author

Multiple Leader Candidate and Competitive Position Allocation for Robust Formation against Member Robot Faults.

Sensors (Basel, Switzerland)·2015

See all related articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Apr 16, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Cooperative environment scans based on a multi-robot system.

¹Yonsei Institute of Convergence Technology, Yonsei University, Songdogwahak-ro, Yeonsu-gu, Incheon 406-840, Korea. bluemichael@yonsei.ac.kr.

Sensors (Basel, Switzerland)

|March 20, 2015

Summary

This study introduces a cooperative environment scan system (CESS) using multiple low-cost robots. This approach offers a cost-effective alternative to single laser scanners, enhancing environmental mapping capabilities.

More Related Videos

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Published on: July 1, 2019

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

Published on: August 4, 2014

Related Experiment Videos

Last Updated: Apr 16, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Published on: July 1, 2019

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

Published on: August 4, 2014

Area of Science:

Robotics
Environmental Sensing
Multi-agent Systems

Background:

Traditional single laser range finders (LRFs) are expensive and have limitations in measurement range and occlusion handling.
Developing cost-effective and robust environmental mapping solutions is crucial for autonomous systems.
Cooperative sensing strategies offer potential to overcome limitations of individual sensors.

Purpose of the Study:

To propose and evaluate a Cooperative Environment Scan System (CESS) using multiple robots with low-cost sensors.
To demonstrate CESS's ability to provide a cost-effective alternative to high-cost single laser scanners.
To show that CESS can extend measurement boundaries and detect occluded obstacles.

Main Methods:

A multi-robot system architecture with a central base robot and multiple child robots equipped with low-cost range finders.
The base robot manages child robot positions, controls their actions, and constructs the environment map.
Child robots collect and relay approximated obstacle information to the base robot.

Main Results:

The proposed CESS effectively accumulates information from multiple low-performance sensors to create a comprehensive environmental map.
Simulation results indicate CESS performance comparable to numerical models of commercial 2D and 3D laser scanners.
The system demonstrated extended measurement boundaries and improved detection of hidden obstacles compared to single sensor systems.

Conclusions:

CESS presents a viable and cost-effective solution for environmental scanning and mapping using distributed, low-cost robotic agents.
The cooperative approach enhances sensing capabilities, overcoming limitations of individual low-performance sensors.
This system offers a scalable and robust alternative for applications requiring detailed environmental awareness.