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

Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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...

You might also read

Related Articles

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

Sort by
Same author

Treatment of proximal and middle one-third humeral fractures with lateral distal tibial helical plate.

European journal of orthopaedic surgery & traumatology : orthopedie traumatologie·2016
Same author

MIF Plays a Key Role in Regulating Tissue-Specific Chondro-Osteogenic Differentiation Fate of Human Cartilage Endplate Stem Cells under Hypoxia.

Stem cell reports·2016
Same author

Tumor Exosomal RNAs Promote Lung Pre-metastatic Niche Formation by Activating Alveolar Epithelial TLR3 to Recruit Neutrophils.

Cancer cell·2016
Same author

Ultra-compact strain- and temperature-insensitive torsion sensor based on a line-by-line inscribed phase-shifted FBG.

Optics express·2016
Same author

The Safety and Immunological Effects of rAd5-EBV-LMP2 Vaccine in Nasopharyngeal Carcinoma Patients: A Phase I Clinical Trial and Two-Year Follow-Up.

Chemical & pharmaceutical bulletin·2016
Same author

Increased Ubqln2 expression causes neuron death in transgenic rats.

Journal of neurochemistry·2016
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: May 10, 2026

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

11.6K

Inspection Robot Navigation Based on Improved TD3 Algorithm.

Bo Huang1, Jiacheng Xie1, Jiawei Yan1

  • 1School of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong 643099, China.

Sensors (Basel, Switzerland)
|April 27, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an improved deep reinforcement learning algorithm (LP-TD3) for mobile robot navigation. It enhances training efficiency and exploration in unfamiliar environments, outperforming existing methods.

Keywords:
curiosity-drivendeep reinforcement learninginspection robot navigationlong- and short-term memory

More Related Videos

Dynamic Navigation for Dental Implant Placement
05:42

Dynamic Navigation for Dental Implant Placement

Published on: September 13, 2022

3.7K
Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

711

Related Experiment Videos

Last Updated: May 10, 2026

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

11.6K
Dynamic Navigation for Dental Implant Placement
05:42

Dynamic Navigation for Dental Implant Placement

Published on: September 13, 2022

3.7K
Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

711

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Machine Learning

Background:

  • Map-based navigation struggles in unfamiliar or dynamic environments.
  • Current deep reinforcement learning (DRL) navigation faces inefficient training and sparse rewards.

Purpose of the Study:

  • To develop an improved DRL algorithm for mobile robot local planning navigation.
  • To address challenges in training efficiency, convergence speed, and reward sparsity in DRL navigation.

Main Methods:

  • Introduced a Long-Short-Term Memory (LSTM) module and Prioritized Experience Replay (PER) for optimized training.
  • Integrated an Intrinsic Curiosity Module (ICM) to combine intrinsic and extrinsic rewards, enhancing exploration.
  • Utilized the two-delay depth deterministic policy gradient (TD3) algorithm as the base framework (LP-TD3).

Main Results:

  • The proposed LP-TD3 method demonstrated superior performance compared to the original algorithm.
  • Improvements were observed across various key performance metrics in simulated environments.

Conclusions:

  • The enhanced LP-TD3 algorithm effectively improves training efficiency and exploratory behavior for mobile robot navigation.
  • This approach offers a promising solution for robust navigation in complex and dynamic environments.