Evidence map›Paper›PMID 42740274›Full record

ArticleSensors (Basel, Switzerland)2026

Decision-Level Multi-Sensor Coordination for Robust Navigation and High-Precision Planar Positioning of Industrial Mobile Robots.

Teng-Xiao Liu, Ming-Wei You, Zi-Yi Zhang, Yan Sun, Cheng-Yuan Liu, Kun Qian, Xue-Yu Lu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Teng-Xiao LiuSchool of Mechanical Engineering, Jiangnan University, Wuxi 214122, China.ORCID 0009-0003-0908-6162
Ming-Wei YouSchool of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China.
Zi-Yi ZhangSchool of Mechanical Engineering, Jiangnan University, Wuxi 214122, China.
Yan SunSchool of Mechanical Engineering, Jiangnan University, Wuxi 214122, China.
Cheng-Yuan LiuSchool of Mechanical Engineering, Jiangnan University, Wuxi 214122, China.ORCID 0009-0007-4331-5490
Kun QianSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China.ORCID 0000-0003-2702-9500
Xue-Yu LuSchool of Mechanical Engineering, Jiangnan University, Wuxi 214122, China.

Funding

National Natural Science Foundation of China 62101455
6 · The paper itself

Abstract

High-precision manufacturing in unstructured factories imposes stringent requirements on real-time scene perception and end-effector positioning accuracy. Traditional single-sensor solutions suffer from perception blind spots in human-robot mixed environments with complex lighting, while chassis cumulative error often leads to rigid collisions during end-effector operations. To address this, this paper proposes and evaluates a decision-level multi-sensor coordination mechanism for robust navigation and high-precision planar positioning of industrial mobile robots. The mechanism assigns explicit sensor roles, distance-dependent trigger conditions, and deterministic safety priorities. At the navigation and obstacle avoidance level, a sequential decision policy is constructed: macroscopically, a lightweight You Only Look Once version 5 small (YOLOv5s) is utilized for the early detection of dynamic objects, providing bounding-box coordinates to trigger preemptive deceleration, while LiDAR independently provides geometric ranging for ROS local-costmap updating and detour replanning; microscopically, a low-level hardware interrupt strategy triggered by ultrasonic sensors is proposed to mitigate near-field blind spots and reduce communication latency. At the end-effector positioning level, under illumination conditions ranging from 200 to 1000 lux, an adaptive alignment algorithm combining hue-saturation-value color-space morphological processing and Kalman filtering is proposed to suppress measurement noise caused by illumination variations and mechanical vibrations. Experiments in the tested dynamic human-robot mixed scenarios showed no rigid collisions for the proposed system and an emergency response time of approximately 50 ms against sudden blind-spot intrusions. Simultaneously, the system achieves a 95% reliability rate in controlling the end-effector 2D planar positioning error (X-Y plane) within a ±2 mm tolerance under complex illumination interference. These results demonstrate improved navigation safety and planar-positioning reliability under the tested flexible-manufacturing conditions.

Indexed as

decision-level multi-sensor coordinationedge computingindustrial mobile robotplanar positioningrobust navigationvisual servoingYOLOv5s

Identifiers

PMID42740274
PMCPMC13567965

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.