Planar Inverse Statics and Path Planning for a Tendon-Driven Discrete Continuum Robot by Yeoun-Jae Kim, Daehan Wi

“…The proposed path planning method achieved an average positional deviation from the reference trajectory ranging from 0.95 mm to 19.77 mm. …”
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A multi strategy bidirectional RRT* algorithm for efficient mobile robot path planning by Yourui Huang, Wenxin Jiang, Shanyong Xu

“…Abstract To address the issues of slow convergence speed and poor path quality of the traditional Rapidly-exploring Random Tree Star (RRT*) algorithm in complex environments, this paper proposes a Multi Strategy Bidirectional RRT* (MS-BI-RRT*) algorithm for efficient mobile robot path planning. …”
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Improved Hybrid A* Algorithm Based on Lemming Optimization for Path Planning of Autonomous Vehicles by Yong Chen, Yuan Liu, Wei Xu

“…The simulation results demonstrate that the proposed method can efficiently avoid obstacles, and its performance is better than that of the traditional hybrid A* algorithm in terms of the computational time and average path length. In a simple scenario, the search time is shortened by 33.2% and the path length is reduced by 11.1%; at the same time, in a complex scenario, the search time is shortened by 23.5% and the path length is reduced by 13.6%.…”
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Multi-Strategy Improved Harris Hawk Optimization Algorithm and Its Application in Path Planning by Chaoli Tang, Wenyan Li, Tao Han, Lu Yu, Tao Cui

“…Finally, MIHHO is applied to robot path planning, and the test results show that in four environments with different complexities and scales, the average path lengths of MIHHO are improved by 1.99%, 14.45%, 4.52%, and 9.19% compared to HHO, respectively. …”
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Adaptive Path Planning for Multi-UAV Systems in Dynamic 3D Environments: A Multi-Objective Framework by Gregorius Airlangga, Ronald Sukwadi, Widodo Widjaja Basuki, Lai Ferry Sugianto, Oskar Ika Adi Nugroho, Yoel Kristian, Radyan Rahmananta

“…This study evaluates and compares the computational performance and practical applicability of advanced path planning algorithms for Unmanned Aerial Vehicles (UAVs) in dynamic and obstacle-rich environments. …”
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An Enhanced Deep Q Network Algorithm for Localized Obstacle Avoidance in Indoor Robot Path Planning by Cheng Chen, Jiantao Yu, Songrong Qian

“…Path planning is a key task in mobile robots, and the application of Deep Q Network (DQN) algorithm for mobile robot path planning has become a hotspot and challenge in current research. …”
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Application of Hybrid Algorithm Based on Ant Colony Optimization and Sparrow Search in UAV Path Planning by Yangyang Tian, Jiaxiang Zhang, Qi Wang, Shanfeng Liu, Zhimin Guo, Huanlong Zhang

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Optimized dual NURBS curve interpolation for high-accuracy five-axis CNC path planning by Yi Xu, Mohd Hairi Mohd Zaman, Feng Zhou

“…In the proposed method, the master curve determines the tool path, while the slave curve adjusts the tool’s posture in real-time. …”
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Rapid Path Planning Algorithm for Percutaneous Rigid Needle Biopsy Based on Optical Illumination Principles by Jian Liu, Shuai Kang, Juan Ren, Dongxia Zhang, Bing Niu, Kai Xu

“…Prolonged processing times increase the risk of patient movement, rendering the planned path invalid. Traditional methods relying on clinician expertise or slow algorithms struggle with complex anatomical modeling for structures such as blood vessels. …”
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Action-Curiosity-Based Deep Reinforcement Learning Algorithm for Path Planning in a Nondeterministic Environment by Junxiao Xue, Jinpu Chen, Shiwen Zhang

“…Extensive experimentation reveals that our enhanced algorithm outperforms conventional methods markedly in terms of success rate and average reward, among other metrics. These experimental outcomes corroborate the proposed method’s robustness and efficacy, laying a solid groundwork for efficient adaptive autonomous path planning within complex and nondeterministic environments.…”
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Global path planning algorithm for mining vehicles integrating simplified visibility graph and A* algorithm by ZHANG Chuanwei, LU Siyan, QIN Peilin, ZHOU Rui, ZHAO Ruiqi, YANG Jiajia, ZHANG Tianle, ZHAO Cong

“…Experimental results indicated that compared to the Complete Visibility Graph + A* algorithm, SVG + A* algorithm, and SVGCA* algorithm, the DVGA* algorithm had the shortest planning time for complex long-distance paths, with average path lengths reduced by 10.79%, 6.26%, and 2.86%, respectively, demonstrating stronger adaptability and higher planning success rates. …”
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A Hybrid Path Planning Algorithm for Orchard Robots Based on an Improved D* Lite Algorithm by Quanjie Jiang, Yue Shen, Hui Liu, Zohaib Khan, Hao Sun, Yuxuan Huang

“…Due to the complex spatial structure, dense tree distribution, and narrow passages in orchard environments, traditional path planning algorithms often struggle with large path deviations, frequent turning, and reduced navigational safety. …”
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Salp Swarm Algorithm Optimized A* Algorithm and Improved B-Spline Interpolation in Path Planning by Hang Zhou, Tianning Shang, Yongchuan Wang, Long Zuo

“…Comparative evaluations across diverse environments confirm the superiority of the proposed method in computational efficiency, path smoothness, and safety. This study presents an effective and robust solution for path planning in complex scenarios.…”
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APPA: An adaptation path planning algorithm for real-time obstacle avoidance in multi-robot systems by Jianzhi Jin, Mou Wu, Ping Fan, Guonian Jin

“…Abstract With the rapid advancement of robotics technology, the deployment of multi-robot systems in logistics, industrial automation, and public services has expanded significantly. However, complex and dynamic environments present stringent requirements for the real-time performance, stability, and coordination capabilities of path planning algorithms. …”
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ARIME-DWA: Robot Path Planning Utilizing Advanced RIME Optimization and Dynamic Windows Approach by Likun Hu, Chengjie Cai

“…Experimental results demonstrate that ARIME outperforms other six algorithms with more robust path planning capabilities. Among them, the average path lengths solved by the ARIME are reduced by 7.7%, 24.5%, and 26.9%, respectively. …”
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Research on Impact of Planned Path Length and Yaw Cost on Collaborative Search of Unmanned Aerial Vehicle Swarms by Heng Zhang, Wenyue Meng, Yanan Liu, Guanyu Liu, Jian Zhang

“…Simulation experiments were conducted for different planned path lengths with or without the inclusion of the yaw cost, analyzing indicators such as the coverage rate, target capture rate, average capture time, and communication and decision-making consumption. …”
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Autonomous Search of Real-Life Environments Combining Dynamical System-Based Path Planning and Unsupervised Learning by Uyiosa Philip Amadasun, Patrick Mcnamee, Zahra Nili Ahmadabadi, Peiman Naseradinmousavi

“…In recent years, advances have been made in chaotic coverage path planning (CCPP) for autonomous search and traversal of spaces with limited environmental cues. …”
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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…To address the challenges of low path planning efficiency for autonomous undersea vehicle(AUV) in multi-target environments, as well as the limitations of the traditional whale optimization algorithm(WOA) in terms of susceptibility to local optima and inadequate adaptability to three-dimensional obstacle avoidance requirements, this study proposed a collaborative planning strategy that integrated a fluid perturbation algorithm with an improved WOA. …”
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A Hybrid ARO Algorithm and Key Point Retention Strategy Trajectory Optimization for UAV Path Planning by Bei Liu, Yuefeng Cai, Duantengchuan Li, Ke Lin, Guanghui Xu

“…An effective path planning algorithm can greatly improve the operational efficiency of UAVs in complex environments like urban and mountainous areas, thus offering more extensive coverage for various tasks. …”
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Informative Path Planning Using Physics-Informed Gaussian Processes for Aerial Mapping of 5G Networks by Jonas F. Gruner, Jan Graßhoff, Carlos Castelar Wembers, Kilian Schweppe, Georg Schildbach, Philipp Rostalski

“…The evaluation results demonstrate that using an appropriate mean function can result in an enhanced prediction accuracy of the GP model and provide a suitable basis for informative path planning. The subsequent informative path-planning simulation experiments highlight these findings. …”
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