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

Hierarchy of Motor Control01:18

Hierarchy of Motor Control

3.2K
The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
3.2K
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

743
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
743
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

441
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
441
Schemas01:42

Schemas

11.8K
A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
11.8K

You might also read

Related Articles

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

Sort by
Same author

Rational design of ultra-inert Gd-DOTABA probes conjugated with unnatural dipeptides for high-contrast and low-dose tumor and vascular MRI.

European journal of medicinal chemistry·2026
Same author

A review of machine learning applications in soil heavy-metal remediation: material design, process optimization, and future challenges.

Environmental geochemistry and health·2026
Same author

Modular Assembly of Bioconjugates Enabled by a Pyridine-Based Chemoselective Sequential Conjugation Platform.

Angewandte Chemie (International ed. in English)·2026
Same author

A Sweet and Stable Strike: Multivalent Glucosylated Gd-DOTBA Conjugate with Ultrahigh Relaxivity for Targeted MRI of Aggressive Cancers.

Journal of medicinal chemistry·2026
Same author

Pyridine-Bridged Axial Coordination Creates Electron-Deficient Co-N<sub>5</sub> Porphyrin Sites for Selective Photoelectrochemical CO<sub>2</sub> Reduction on Si Nanowires.

The journal of physical chemistry letters·2026
Same author

ILDR2 impairs antitumor surveillance by recruiting immunosuppressive CCR2<sup>+</sup> monocytes.

Biochemical and biophysical research communications·2026

Related Experiment Video

Updated: Aug 27, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

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

Published on: October 14, 2017

11.8K

Hierarchical framework for mobile robots to effectively and autonomously explore unknown environments.

Xuehao Sun1, Shuchao Deng2, Baohong Tong2

  • 1School of Mechanical Engineering, Anhui University of Technology, Ma'anshan 243032, China.

ISA Transactions
|September 24, 2022
PubMed
Summary

This study introduces a new autonomous exploration framework for robots in unknown environments. It enhances exploration efficiency and ensures safety through a novel motion planning approach.

Keywords:
Autonomous explorationMobile robotMotion planningObstacle avoidance

More Related Videos

Robotic Sensing and Stimuli Provision for Guided Plant Growth
08:02

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Published on: July 1, 2019

8.1K
Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

14.7K

Related Experiment Videos

Last Updated: Aug 27, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

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

Published on: October 14, 2017

11.8K
Robotic Sensing and Stimuli Provision for Guided Plant Growth
08:02

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Published on: July 1, 2019

8.1K
Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect
09:00

Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

Published on: December 19, 2016

14.7K

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Autonomous Systems

Background:

  • Autonomous exploration in unknown environments presents significant challenges in robotics.
  • Current methods often lack efficiency and safety guarantees due to random or greedy strategies.
  • Robots struggle to gather sufficient environmental data and ensure safety in unfamiliar territories.

Purpose of the Study:

  • To propose an advanced autonomous exploration motion planning framework.
  • To enhance both the efficiency and safety of robotic exploration in unknown environments.
  • To address limitations of existing exploration strategies.

Main Methods:

  • Developed a two-level motion planning framework: exploration and obstacle avoidance.
  • Exploration level utilizes a forward filtering angle and cost function to identify optimal frontier targets, maximizing movement into unknown areas.
  • Obstacle avoidance level employs a scenario-speed conversion mechanism, dynamically planning motion based on target and obstacle information for safety.

Main Results:

  • The proposed framework significantly improves exploration efficiency by guiding robots towards unknown areas.
  • The dynamic obstacle avoidance mechanism ensures a high level of safety during exploration.
  • Experimental results in simulations and real-world scenarios demonstrate the method's superiority over existing approaches.

Conclusions:

  • The novel framework effectively balances exploration efficiency and safety in unknown environments.
  • The independent yet interconnected exploration and obstacle avoidance levels provide a robust solution.
  • This research advances the capabilities of autonomous robots in complex, uncharted territories.