ReviewSensors (Basel, Switzerland)2025
Path Planning Trends for Autonomous Mobile Robot Navigation: A Review.
Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed.
- SFPathFormer for spatial frequency robot navigation and obstacle avoidance.Scientific reports · 2026Article
- Teardrop Risk Field-Based Spatiotemporal Path Planning Method for Mobile Robots in Dynamic Environments.Sensors (Basel, Switzerland) · 2026Article
- Solving the 3D UAV Path Planning Problem Using an Improved Multi-Leader Multi-Objective Whale Optimization Algorithm.Biomimetics (Basel, Switzerland) · 2026Article
- CBAM meets DropBlock: enhancing robot steering-angle prediction with hybrid attention and structured dropout.Scientific reports · 2026Article
- Global Path Planning Methods Based on the Relationship Between Traversability Capability and Terrain Matching.Sensors (Basel, Switzerland) · 2026Article
- A review of full-stack autonomous obstacle avoidance for assistive robots for the disabled.Frontiers in robotics and AI · 2026Review
- Self-adaptive search algorithm for path planning based on the A* algorithm.Scientific reports · 2025Article
- QL-HIT2F: A Q-Learning-Aided Adaptive Fuzzy Path Planning Algorithm with Enhanced Obstacle Avoidance.Sensors (Basel, Switzerland) · 2025Article
- Evaluating the Impact of Aggregation Operators on Fuzzy Signatures for Robot Path Planning.Sensors (Basel, Switzerland) · 2025Article
- DPDQN-TER: An Improved Deep Reinforcement Learning Approach for Mobile Robot Path Planning in Dynamic Scenarios.Sensors (Basel, Switzerland) · 2025Article
- A Multi-Strategy Improved Zebra Optimization Algorithm for AGV Path Planning.Biomimetics (Basel, Switzerland) · 2025Article
- Development of a Dynamic Path Planning System for Autonomous Mobile Robots Using a Multi-Agent System Approach.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
With the development of robotics technology, there is a growing demand for robots to perform path planning autonomously. Therefore, rapidly and safely planning travel routes has become an important research direction for autonomous mobile robots. This paper elaborates on traditional path-planning algorithms and the limitations of these algorithms in practical applications. Meanwhile, in response to these limitations, it reviews the current research status of recent improvements to these traditional algorithms. The results indicate that these improved path-planning algorithms perform well in tests or practical applications, and multi-algorithm fusion for path planning outperforms single-algorithm path planning.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.