Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Classification of Signals01:30

Classification of Signals

1.1K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.1K
Classification of Systems-I01:26

Classification of Systems-I

441
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
441
Force Classification01:22

Force Classification

2.0K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
2.0K
Classification of Systems-II01:31

Classification of Systems-II

371
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
371

You might also read

Related Articles

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

Sort by
Same author

Accuracy of 3 Intraoral and 1 Extraoral Digital Scanning Systems for Multiple Laminate Veneer Preparations: An In Vitro Study.

Medical science monitor : international medical journal of experimental and clinical research·2026
Same author

Robotic technologies in prosthodontics and implantology: a scoping review of current applications and future directions.

BMC oral health·2026
Same author

Anterior loop of the mental nerve: a cone-beam computed tomography analysis of its prevalence and surgical implications in implant dentistry.

Folia morphologica·2026
Same author

Post-polymerization dimensional accuracy of fast and superfast vinylpolysiloxane-based jaw relation recording materials: An in vitro study.

Journal of applied biomaterials & functional materials·2026
Same author

Pellet Printing for Soft Robotic Devices.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Correction: Hassan et al. Influence of Surface Treatment and Protracted Ageing on the Shear Bond Strength of Orthodontic Brackets to Two Digitally Fabricated (Milled and 3D-Printed) Polymethacrylate-Based Provisional Crowns. <i>Polymers</i> 2025, <i>17</i>, 699.

Polymers·2026
Same journal

Passive wheels on legged robots: a survey.

Frontiers in robotics and AI·2026
Same journal

Politeness cannot make up for robots' errors.

Frontiers in robotics and AI·2026
Same journal

Workers expect basic social skills but limited autonomy from future robots - a qualitative interview study and taxonomy for robot social skills.

Frontiers in robotics and AI·2026
Same journal

Human-robot interaction in sustainable hospitality: how robot type shapes customer emotions, green perceptions, and service loyalty.

Frontiers in robotics and AI·2026
Same journal

Dynamic variance-aware federated tuning for efficient autonomous vehicle perception under non-IID settings.

Frontiers in robotics and AI·2026
Same journal

Editorial: Synergizing large language models and computational intelligence for advanced robotic systems.

Frontiers in robotics and AI·2026
See all related articles

Related Experiment Video

Updated: Nov 19, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

5.7K

Multi-Functional Sensing for Swarm Robots Using Time Sequence Classification: HoverBot, an Example.

Markus P Nemitz1,2, Ryan J Marcotte2, Mohammed E Sayed1

  • 1School of Engineering, Institute for Integrated Micro and Nano Systems, The University of Edinburgh, Edinburgh, United Kingdom.

Frontiers in Robotics and AI
|January 27, 2021
PubMed
Summary
This summary is machine-generated.

This study enhances low-cost robot swarms by enabling a single Hall-effect sensor to detect movement, rotation, and collisions. This approach boosts robot functionality without increasing costs, aiding scalable swarm robotics research.

Keywords:
DBADTWHoverBotbarycentre averagingdynamic time warpingmulti-functional sensingswarm robotics

More Related Videos

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches
07:23

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

Published on: August 4, 2014

23.5K
Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.5K

Related Experiment Videos

Last Updated: Nov 19, 2025

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

5.7K
Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches
07:23

Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

Published on: August 4, 2014

23.5K
Flying Insect Detection and Classification with Inexpensive Sensors
05:16

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

25.5K

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Sensor Technology

Background:

  • Scaling robot swarms to thousands of units is hindered by limitations in sensing, processing, and locomotion capabilities of low-cost robots.
  • Existing low-cost robotic systems often have restricted functionalities, limiting the scope of research experiments.
  • Increasing robot functionality typically involves adding components, which raises costs and hinders scalability.

Purpose of the Study:

  • To demonstrate how low-cost hardware can be utilized beyond its standard functionality for enhanced robot capabilities.
  • To enable a single Hall-effect sensor on the HoverBot system to detect movement, rotation, and collisions.
  • To develop a method for increasing robot functionality while retaining low cost for scalable swarm robotics.

Main Methods:

  • Systematic review and analysis of sensing capabilities in 15 swarm robotic systems using a general sensor model.
  • Development of a time series classifier based on magnetic field readouts from the HoverBot's Hall-effect sensor.
  • Modification and application of signal processing techniques for online classification of time-variant magnetic field measurements on a low-cost microcontroller.

Main Results:

  • HoverBot's Hall-effect sensor magnetic field readouts were successfully associated with movement, rotation, and collision events.
  • A time series classifier was built and implemented on the HoverBot's microcontroller for online sensing.
  • The HoverBot system was enabled with sensing capabilities for successful movement, rotation, and collision detection using its single Hall-effect sensor.

Conclusions:

  • A single Hall-effect sensor can provide multiple sensing capabilities (movement, rotation, collision) in low-cost robots.
  • The developed classification method offers a cost-effective way to enhance robot functionality for scalable swarm robotics.
  • This approach can be applied to other sensors and systems to increase robot capabilities without compromising cost-effectiveness.