Search research 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

Related Concept Videos

Survey Safety

Survey Safety

Surveying near highways, rough terrain, or power lines involves significant risks. Working along highways is particularly dangerous and requires the use of warning signs and flagmen. It is safest to avoid working directly on roads and use offsets whenever possible. When highway work is unavoidable, it must follow all safety guidelines. Surveyors should wear bright clothing, such as orange reflective vests, to ensure visibility to motorists, coworkers, and hunters. In construction zones, wearing...

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...

You might also read

Related Articles

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

Sort by

Same author

Synergistic integration of ripple filter and penumbra reduction for enhanced dose conformity and beam delivery efficiency in proton therapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026

Same author

Microglial Pruning of Excitatory Synapses in the Hippocampus Is Complement C3-Independent in Physiological and Neuroinflammatory States.

Glia·2026

Same author

Biomarkers for oesophageal squamous cell carcinoma and the role of HPV: Multi‑omics approaches and current evidence (Review).

International journal of oncology·2026

Same author

Finite-Element Comparison of a Proximal Femoral Laterally Bionic Intramedullary Nail (PFLBN) Versus PFNA and PFBN for AO/OTA 31-A3.1 Intertrochanteric Fractures.

Orthopaedic surgery·2026

Same author

Assessing P1NP/β-CTX as Potential Risk Factors Associated With Different Subtypes of Fragile Hip Fracture in Elderly Patients.

Orthopaedic surgery·2026

Same author

Immunosensors for ovarian cancer detection.

Clinica chimica acta; international journal of clinical chemistry·2026

Search research articles

Related Experiment Video

Updated: Jul 10, 2025

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Published on: July 1, 2019

A New Assistance Navigation Method for Substation Inspection Robots to Safely Cross Grass Areas.

Qiang Yang^1,2, Song Ma¹, Gexiang Zhang¹

¹School of Automation, Chengdu University of Information Technology, Chengdu 610225, China.

Sensors (Basel, Switzerland)

|November 25, 2023

Summary

This study introduces an improved navigation method for substation inspection robots to safely cross grass obstacles. The new algorithm enhances object detection and fuses sensor data, boosting inspection efficiency.

Keywords:

assistant navigation algorithm faster-RCNN grass recognition inspection robot

More Related Videos

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement

Published on: May 11, 2020

Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay

Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay

Published on: February 24, 2023

Related Experiment Videos

Last Updated: Jul 10, 2025

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Robotic Sensing and Stimuli Provision for Guided Plant Growth

Published on: July 1, 2019

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement

A Spine Robotic-Assisted Navigation System for Pedicle Screw Placement

Published on: May 11, 2020

Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay

Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay

Published on: February 24, 2023

Area of Science:

Robotics and Automation
Artificial Intelligence
Substation Engineering

Background:

Intelligent substations utilize inspection robots for safe operation.
Grass obstacles frequently interrupt robot inspections, reducing efficiency.
Current LiDAR-based robots misidentify grass as hard obstacles, causing task failures.

Purpose of the Study:

To develop an advanced navigation method for substation inspection robots to safely traverse grass areas.
To enhance the recognition of grass as a distinct obstacle type.
To improve the accuracy of object detection and overall inspection efficiency.

Main Methods:

Designed an assistant navigation algorithm for grass recognition and obstacle crossing.
Improved the Faster R-CNN network with a three-layer convolutional structure for optimized object detection boxes.
Fused ultrasonic radar signals with object recognition results for safety judgments.

Main Results:

The improved Faster R-CNN achieved a mean Average Precision (mAP) of 91.25% at an IoU threshold of 0.5.
The proposed method demonstrated a 4.13% mAP improvement over the basic network.
The navigation algorithm successfully enabled robots to safely cross grass areas, enhancing inspection efficiency.

Conclusions:

The developed assistant navigation method effectively enables substation inspection robots to overcome grass obstacles.
The optimized Faster R-CNN network significantly improves object detection accuracy in grassy environments.
This approach enhances the reliability and efficiency of automated substation inspections.