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Application of A* Algorithm for Real-time Path Re-planning of an Unmanned Surface Vehicle Avoiding Underwater Obstacles 认领 引用 被引量：10
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作者 Thanapong Phanthong Toshihiro Maki +2 位作者 Tamaki Ura Takashi Sakamaki Pattara Aiyarak 《Journal of Marine Science and Application》 2014年第1期105-116,共12页
This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle(USV) based on multi-beam forward looking sonar(FLS). Near-optimal paths in static and dynamic environment... This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle(USV) based on multi-beam forward looking sonar(FLS). Near-optimal paths in static and dynamic environments with underwater obstacles are computed using a numerical solution procedure based on an A* algorithm. The USV is modeled with a circular shape in 2 degrees of freedom(surge and yaw). In this paper, two-dimensional(2-D) underwater obstacle avoidance and the robust real-time path re-planning technique for actual USV using multi-beam FLS are developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames in the field of view of the sonar with a proper update frequency of the FLS. The performance of the proposed method was verified through simulations, and sea experiments. For simulations, the USV model can avoid both a single stationary obstacle, multiple stationary obstacles and moving obstacles with the near-optimal trajectory that are performed both in the vehicle and the world reference frame. For sea experiments, the proposed method for an underwater obstacle avoidance system is implemented with a USV test platform. The actual USV is automatically controlled and succeeded in its real-time avoidance against the stationary undersea obstacle in the field of view of the FLS together with the Global Positioning System(GPS) of the USV. 展开更多
关键词 underwater obstacle avoidance real-time pathre-planning A＊ algorithm sonar image unmanned surface vehicle
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Improved Dijkstra Algorithm for Mobile Robot Path Planning and Obstacle Avoidance 认领 引用 被引量：44
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作者 Shaher Alshammrei Sahbi Boubaker Lioua Kolsi 《Computers, Materials & Continua》 SCIE EI 2022年第9期5939-5954,共16页
Optimal path planning avoiding obstacles is among the most attractive applications of mobile robots(MRs)in both research and education.In this paper,an optimal collision-free algorithm is designed and implemented prac... Optimal path planning avoiding obstacles is among the most attractive applications of mobile robots(MRs)in both research and education.In this paper,an optimal collision-free algorithm is designed and implemented practically based on an improved Dijkstra algorithm.To achieve this research objectives,first,the MR obstacle-free environment is modeled as a diagraph including nodes,edges and weights.Second,Dijkstra algorithm is used offline to generate the shortest path driving the MR from a starting point to a target point.During its movement,the robot should follow the previously obtained path and stop at each node to test if there is an obstacle between the current node and the immediately following node.For this aim,the MR was equipped with an ultrasonic sensor used as obstacle detector.If an obstacle is found,the MR updates its diagraph by excluding the corresponding node.Then,Dijkstra algorithm runs on the modified diagraph.This procedure is repeated until reaching the target point.To verify the efficiency of the proposed approach,a simulation was carried out on a hand-made MR and an environment including 9 nodes,19 edges and 2 obstacles.The obtained optimal path avoiding obstacles has been transferred into motion control and implemented practically using line tracking sensors.This study has shown that the improved Dijkstra algorithm can efficiently solve optimal path planning in environments including obstacles and that STEAM-based MRs are efficient cost-effective tools to practically implement the designed algorithm. 展开更多
关键词 Mobile robot(MR) STEAM path planning obstacle avoidance improved dijkstra algorithm
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Obstacle avoidance for multi-missile network via distributed coordination algorithm 认领 引用 被引量：17
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作者 Zhao Jiang Zhou Rui 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2016年第2期441-447,共7页
A distributed coordination algorithm is proposed to enhance the engagement of the multi-missile network in consideration of obstacle avoidance. To achieve a cooperative interception, the guidance law is developed in a... A distributed coordination algorithm is proposed to enhance the engagement of the multi-missile network in consideration of obstacle avoidance. To achieve a cooperative interception, the guidance law is developed in a simple form that consists of three individual components for tar- get capture, time coordination and obstacle avoidance. The distributed coordination algorithm enables a group of interceptor missiles to reach the target simultaneously, even if some member in the multi-missile network can only collect the information from nearest neighbors. The simula- tion results show that the guidance strategy provides a feasible tool to implement obstacle avoid- ance for the multi-missile network with satisfactory accuracy of target capture. The effects of the gain parameters are also discussed to evaluate the proposed approach. 展开更多
关键词 Cooperative guidance Distributed algorithms Impact time Missile guidance Multiple missiles Obstacle avoidance Proportional navigation
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Distance Control Algorithm for Automobile Automatic Obstacle Avoidance and Cruise System 认领 引用 被引量：3
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作者 Jinguo Zhao 《Computer Modeling in Engineering & Sciences》 SCIE EI 2018年第7期69-88,共20页
With the improvement of automobile ownership in recent years,the incidence of traffic accidents constantly increases and requirements on the security of automobiles become increasingly higher.As science and technology... With the improvement of automobile ownership in recent years,the incidence of traffic accidents constantly increases and requirements on the security of automobiles become increasingly higher.As science and technology develops constantly,the development of automobile automatic obstacle avoidance and cruise system accelerates gradually,and the requirement on distance control becomes stricter.Automobile automatic obstacle avoidance and cruise system can determine the conditions of automobiles and roads using sensing technology,automatically adopt measures to control automobile after discovering road safety hazards,thus to reduce the incidence of traffic accidents.To prevent accidental collision of automobile which are installed with automatic obstacle avoidance and cruise system,active brake should be controlled during driving.This study put forward a neural network based proportional-integral-derivative(PID)control algorithm.The active brake of automobiles was effectively controlled using the system to keep the distance between automobiles.Moreover the algorithm was tested using professional automobile simulation platform.The results demonstrated that neural network based PID control algorithm can precisely and efficiently control the distance between two cars.This work provides a reference for the development of automobile automatic obstacle avoidance and cruise system. 展开更多
关键词 Obstacle avoidance and cruise distance control automobile algorithm
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LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment 认领 引用 被引量：2
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作者 Xiaoli Li Tongtong Jiao +2 位作者 Jinfeng Ma Dongxing Duan Shengbin Liang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第1期595-617,共23页
In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone ... In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account. 展开更多
关键词 Unmanned surface vehicles local obstacle avoidance algorithm artificial potential field algorithm path planning collision detection
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A Lightweight UAV Visual Obstacle Avoidance Algorithm Based on Improved YOLOv8 认领 引用 被引量：2
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作者 Zongdong Du Xuefeng Feng +2 位作者 Feng Li Qinglong Xian Zhenhong Jia 《Computers, Materials & Continua》 SCIE EI 2024年第11期2607-2627,共21页
The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightwei... The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightweight YOLOv8-based obstacle detection algorithm optimized for UAV obstacle avoidance.The algorithm enhances the detection capability for small and irregular obstacles by removing the P5 feature layer and introducing deformable convolution v2(DCNv2)to optimize the cross stage partial bottleneck with 2 convolutions and fusion(C2f)module.Additionally,it reduces the model’s parameter count and computational load by constructing the unite ghost and depth-wise separable convolution(UGDConv)series of lightweight convolutions and a lightweight detection head.Based on this,we designed a visual obstacle avoidance algorithm that can improve the obstacle avoidance performance of UAVs in different environments.In particular,we propose an adaptive distance detection algorithm based on obstacle attributes to solve the ranging problem for multiple types and irregular obstacles to further enhance the UAV’s obstacle avoidance capability.To verify the effectiveness of the algorithm,the UAV obstacle detection(UAD)dataset was created.The experimental results show that UAD-YOLOv8 improves mAP50 by 3.4%and reduces GFLOPs by 34.5%compared to YOLOv8n while reducing the number of parameters by 77.4%and the model size by 73%.These improvements significantly enhance the UAV’s obstacle avoidance performance in complex environments,demonstrating its wide range of applications. 展开更多
关键词 Unmanned aerial vehicle obstacle detection obstacle avoidance algorithm
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Dynamic A^*path finding algorithm and 3D lidar based obstacle avoidance strategy for autonomous vehicles 认领 引用 被引量：3
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作者 Wang Xiaohua Ma Pin +1 位作者 Wang Hua Li Li 《High Technology Letters》 EI CAS 2020年第4期383-389,共7页
This paper presents a novel dynamic A^*path finding algorithm and 3D lidar based local obstacle avoidance strategy for an autonomous vehicle.3D point cloud data is collected and analyzed in real time.Local obstacles a... This paper presents a novel dynamic A^*path finding algorithm and 3D lidar based local obstacle avoidance strategy for an autonomous vehicle.3D point cloud data is collected and analyzed in real time.Local obstacles are detected online and a 2D local obstacle grid map is constructed at 10 Hz/s.The A^*path finding algorithm is employed to generate a local path in this local obstacle grid map by considering both the target position and obstacles.The vehicle avoids obstacles under the guidance of the generated local path.Experiment results have shown the effectiveness of the obstacle avoidance navigation algorithm proposed. 展开更多
关键词 autonomous navigation local obstacle avoidance dynamic A*path finding algorithm point cloud processing local obstacle map
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Swarm intelligence based dynamic obstacle avoidance for mobile robots under unknown environment using WSN 认领 引用 被引量：4
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作者 薛晗 马宏绪 《Journal of Central South University of Technology》 2008年第6期860-868,共9页
To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathem... To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. Ant colony optimization (ACO) algorithm based on bionic swarm intelligence was used for solution of the multi-objective optimization. Energy consumption and topology of the WSN were also discussed. A practical implementation with real WSN and real mobile robots were carried out. In environment with multiple obstacles, the convergence curve of the shortest path length shows that as iterative generation grows, the length of the shortest path decreases and finally reaches a stable and optimal value. Comparisons show that using sensor information fusion can greatly improve the accuracy in comparison with single sensor. The successful path of robots without collision validates the efficiency, stability and accuracy of the proposed algorithm, which is proved to be better than tradition genetic algorithm (GA) for dynamic obstacle avoidance in real time. 展开更多
关键词 wireless sensor network dynamic obstacle avoidance mobile robot ant colony algorithm swarm intelligence path planning navigation
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Obstacle avoidance technology of bionic quadruped robot based on multi-sensor information fusion 认领 引用
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作者 韩宝玲 张天 +2 位作者 罗庆生 朱颖 宋明辉 《Journal of Beijing Institute of Technology》 EI CAS 2016年第4期448-454,共7页
In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was stu... In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was studied under the condition that the robot moves in the Walk gait on a structured road. Firstly, the distance information of obstacles from these two sensors was separately processed by the Kalman filter algorithm, which largely reduced the noise interference. After that, we obtained two groups of estimated distance values from the robot to the obstacle and a variance of the estimation value. Additionally, a fusion of the estimation values and the variances was achieved based on the STF fusion algorithm. Finally, a simulation was performed to show that the curve of a real value was tracked well by that of the estimation value, which attributes to the effectiveness of the Kalman filter algorithm. In contrast to statistics before fusion, the fusion variance of the estimation value was sharply decreased. The precision of the position information is 4. 6 cm, which meets the application requirements of the robot. 展开更多
关键词 multi-sensor Kalman filter algorithm constant velocity （CV） model STF fusion algo-rithm obstacle avoidance of robot
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A comprehensive review of obstacle avoidance for autonomous agricultural machinery in multi-operational environment 认领 引用 被引量：1
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作者 Zhijian Chen Jianjun Yin +4 位作者 Sheikh Muhammad Farhan Lu Liu Ding Zhang Maile Zhou Junhui Cheng 《Artificial Intelligence in Agriculture》 SCIE EI CSCD 2026年第1期139-163,共25页
As automation becomes increasingly adopted to mitigate labor shortages and boost productivity,autonomous technologies such as tractors,drones,and robotic devices are being utilized for various tasks that include plowi... As automation becomes increasingly adopted to mitigate labor shortages and boost productivity,autonomous technologies such as tractors,drones,and robotic devices are being utilized for various tasks that include plowing,seeding,irrigation,fertilization,and harvesting.Successfully navigating these changing agricultural landscapes necessitates advanced sensing,control,and navigation systems that can adapt in real time to guarantee effective and safe operations.This review focuses on obstacle avoidance systems in autonomous farming machinery,highlighting multi-functional capabilities within intricate field settings.It analyzes various sensing technologies,LiDAR,visual cameras,radar,ultrasonic sensors,GPS/GNSS,and inertial measurement units(IMU)for their individual and collective contributions to precise obstacle detection in fluctuating field conditions.The review examines the potential of multi-sensor fusion to enhance detection accuracy and reliability,with a particular emphasizing on achieving seamless obstacle recognition and response.It addresses recent advancements in control and navigation systems,particularly focusing on path-planning algorithms and real-time decision-making.It enables autonomous systems to adjust dynamically across multi-functional agricultural environments.The methodologies used for path planning,including adaptive and learning-based strategies,are discussed for their ability to optimize navigation in complicated field conditions.Real-time decision-making frameworks are similarly evaluated for their capacity to provide prompt,data-driven reactions to changing obstacles,which is critical for maintaining operational efficiency.Moreover,this review discusses environmental and topographical challenges like variable terrain,unpredictable weather,complex crop arrangements,and interference from co-located machinery that hinder obstacle detection and necessitate adaptive,resilient system responses.In addition,the paper emphasizes future research opportunities,highlighting the significance of advancements in multi-sensor fusion,deep learning for perception,adaptive path planning,model-free control strategies,artificial intelligence,and energy-efficient designs.Enhancing obstacle avoidance systems enables autonomous agricultural machinery to transform modern farming by increasing efficiency,precision,and sustainability.The review highlights the potential of these technologies to support global efforts for sustainable agriculture and food security,aligning agricultural innovation with the needs of a swiftly growing population. 展开更多
关键词 Autonomous navigation Obstacle avoidance Precision agriculture Path planning algorithms Multi-sensor fusion
基于改进APF-RRT的采摘机械臂运动路径规划 认领 引用 被引量：2
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作者 贾通 潘星宇 +3 位作者 钱振东 路红 李佩娟 张文 《农机化研究》 北大核心 2026年第2期173-182,共10页
在农业自动化快速发展的背景下,机械臂作为果园智能采摘作业的核心设备,其路径规划能力直接影响作业效率。然而果园环境复杂,传统人工势场法(APF)、快速随机搜索树(RRT)等路径规划算法在避障能力与运动平滑等方面仍存在一定不足,难以满... 在农业自动化快速发展的背景下,机械臂作为果园智能采摘作业的核心设备,其路径规划能力直接影响作业效率。然而果园环境复杂,传统人工势场法(APF)、快速随机搜索树(RRT)等路径规划算法在避障能力与运动平滑等方面仍存在一定不足,难以满足高效、安全的采摘需求。针对上述问题,提出了一种基于改进APF-RRT的路径规划算法。通过人工势场引导目标采样方向,增强路径趋近性,并引入非线性斥力场模型平滑势能分布,缓解斥力突变导致的局部震荡;同时,设计了基于最小障碍距离的动态步长策略,自适应调整采样粒度,以兼顾搜索效率和避障精度;通过障碍可行性检测方法去除冗余节点,结合三次B样条曲线实现路径平滑处理,提升路径连续性与执行稳定性。试验表明:在二维空间环境下,改进APF-RRT算法较RRT与APF-RRT算法分别缩短耗时78.75%、58.99%,路径长度减少16.88%、5.93%;在三维空间环境下,耗时缩短88.85%、65.20%,路径长度减少19.60%、5.61%;在机械臂仿真环境中,改进算法生成的路径更加平滑,转折点数量减少。研究结果验证了改进APF-RRT算法在复杂果园下具备良好的全局搜索与避障能力,以及较好的有效性与稳定性。 展开更多
关键词 采摘机械臂 路径规划 人工势场法 快速随机搜索树 改进APF-RRT算法 避障
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基于改进RRT算法的采摘机械臂路径规划研究 认领 引用 被引量：2
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作者 孙波 彭浩 +2 位作者 周健康 陈红明 赵伟 《农机化研究》 北大核心 2026年第3期169-177,共9页
为了使采摘机械臂在复杂环境下完成采摘任务,提出了改进RRT算法有效规划机器臂路径,以提高机械臂的避障能力。针对标准RRT算法在多自由度机械臂路径规划中存在规划耗时长、导向性较差,冗余节点多和路径质量差等问题,引入动态采样域策略... 为了使采摘机械臂在复杂环境下完成采摘任务,提出了改进RRT算法有效规划机器臂路径,以提高机械臂的避障能力。针对标准RRT算法在多自由度机械臂路径规划中存在规划耗时长、导向性较差,冗余节点多和路径质量差等问题,引入动态采样域策略和目标偏置概率策略,提高了算法的导向性和收敛速度。设置了机械臂路径规划的两种仿真实验环境,包含多个小球体的小型障碍物环境和一个大球体的大型障碍物环境,并进行仿真对比实验。在小型障碍物环境下的仿真结果表明,相比GB-RRT算法,改进算法的时间代价减少了87.79%、最终路径的节点数减少了95.08%、路径代价减少了14.63%;在大型障碍物环境下的仿真结果表明,GB-RRT算法路径规划失败,而改进算法能够规划出一条合理的路径,使机械臂顺利避开障碍物。 展开更多
关键词 采摘机械臂 路径规划 RRT避障算法 动态采样域策略 B样条曲线
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基于改进JPS和DWA算法的移动机器人路径规划 认领 引用 被引量：3
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作者 程博 蔡龙帅 +1 位作者 郭桂芳 张烜 《郑州大学学报（工学版）》 CAS 北大核心 2026年第3期47-56,共10页
针对传统跳点搜索(JPS)算法在路径规划过程中因访问大量无关扩展节点而致使搜索盲目性增强、内存占用增大,以及输出路径存在冗余节点等问题,提出了一种基于目标点搜索方向优先级和动态权重评价函数的改进JPS算法。首先,依据目标点与移... 针对传统跳点搜索(JPS)算法在路径规划过程中因访问大量无关扩展节点而致使搜索盲目性增强、内存占用增大,以及输出路径存在冗余节点等问题,提出了一种基于目标点搜索方向优先级和动态权重评价函数的改进JPS算法。首先,依据目标点与移动机器人的位置关系,提升算法寻路时目标点所在方向的优先级,并引入基于距离的动态权重评价函数,以此减少搜索无关节点造成的资源浪费和效率损耗;其次,对改进后的JPS算法输出的全局路径实施二次规划,消除原路径中存在的冗余节点,使全局路径更为平滑;再次,引入并改进动态窗口法(DWA)算法作为局部路径规划算法,改进后的DWA算法将采用基于碰撞距离的动态优先级策略,自动避让交叉路径上的移动机器人;最后,分别对改进后的JPS算法和DWA算法进行仿真验证。结果表明:相较于传统跳点算法,所提算法搜索到的扩展节点数平均减少了60.0%,轨迹节点数平均减少了43.6%,路径拐点数平均减少了23.9%。此外,改进后的DWA算法能够有效解决传统DWA算法在处理路径冲突等动态环境问题时存在的缺陷与不足,显著提高了DWA算法在多机器人路径规划中的协同性和适应性。 展开更多
关键词 跳点搜索算法 路径规划 优先级避障 动态权重评价函数 冲突路径
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A novel obstacle avoidance heuristic algorithm of continuum robot based on FABRIK 认领 引用 被引量：2
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作者 WU HaoRan YU JingJun +1 位作者 PAN Jie PEI Xu 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2022年第12期2952-2966,共15页
Obstacle avoidance and path planning of continuum robots are challenging tasks due to the hyper-redundant degree of freedoms(DOFs)and restricted working environments.Meanwhile,most current heuristic algorithm-based ob... Obstacle avoidance and path planning of continuum robots are challenging tasks due to the hyper-redundant degree of freedoms(DOFs)and restricted working environments.Meanwhile,most current heuristic algorithm-based obstacle avoidance algorithms exist with low computational efficiency,complex solution process,and inability to add global constraints.This paper proposes a novel obstacle avoidance heuristic algorithm based on the forward and backward reaching inverse kinematics(FABRIK)algorithm.The update of key nodes in this algorithm is modeled as the movement of charges in an electric field,avoiding complex nonlinear operations.The algorithm achieves the robustness of inverse kinematics and path tracking in complex environments by imposing constraints on key nodes and determining the location of obstacles in advance.This algorithm is characterized by a high convergence rate,low computational cost,and can be used for real-time applications.The proposed approach also has wide applicability and can be applied to both mobile and fixed-base continuum robots.And it can be further extended to the field of hyper-redundant robots.The algorithm's effectiveness is further validated by simulating the path tracking and obstacle avoidance of a five-segment continuum robot in various environments and comparisons with classical methods. 展开更多
关键词 continuum robot FABRIK algorithm obstacle avoidance motion planning
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Development of Wave Water Simulator for Path Planning of Autonomous Robots in Constrained Environments 认领 引用
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作者 Hui Chen Mohammed A.H.Ali +6 位作者 Bushroa Abd Razak Zhenya Wang Yusoff Nukman Shikai Zhang Zhiwei Huang Ligang Yao Mohammad Alkhedher 《Computers, Materials & Continua》 SCIE EI 2026年第4期2357-2385,共29页
Most existing path planning approaches rely on discrete expansions or localized heuristics that can lead to extended re-planning,inefficient detours,and limited adaptability to complex obstacle distributions.These iss... Most existing path planning approaches rely on discrete expansions or localized heuristics that can lead to extended re-planning,inefficient detours,and limited adaptability to complex obstacle distributions.These issues are particularly pronounced when navigating cluttered or large-scale environments that demand both global coverage and smooth trajectory generation.To address these challenges,this paper proposes a Wave Water Simulator(WWS)algorithm,leveraging a physically motivated wave equation to achieve inherently smooth,globally consistent path planning.In WWS,wavefront expansions naturally identify safe corridors while seamlessly avoiding local minima,and selective corridor focusing reduces computational overhead in large or dense maps.Comprehensive simulations and real-world validations-encompassing both indoor and outdoor scenarios-demonstrate that WWS reduces path length by 2%-13%compared to conventional methods,while preserving gentle curvature and robust obstacle clearance.Furthermore,WWS requires minimal parameter tuning across diverse domains,underscoring its broad applicability to warehouse robotics,field operations,and autonomous service vehicles.These findings confirm that the proposed wave-based framework not only bridges the gap between local heuristics and global coverage but also sets a promising direction for future extensions toward dynamic obstacle scenarios and multi-agent coordination. 展开更多
关键词 PDE-based wave propagation robot path planning obstacle avoidance wave water simulator laser simulator(LS)and generalized laser simulator(GLS) A*algorithm
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基于改进时间弹性带算法的局部路径规划 认领 引用
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作者 胡欣 张家钟 +3 位作者 胡帅 肖剑 罗诗伟 马亮 《浙江大学学报（工学版）》 EI CAS CSCD 北大核心 2026年第4期702-711,共10页
针对时间弹性带(TEB)算法在复杂环境下出现加速度变化率突变、控制指令不平滑的问题,提出改进的TEB算法.在原始TEB算法基础上引入加加速度(jerk)约束来平滑速度和加速度曲线,避免机器人在运动过程中发生震荡、抖动现象.采用自适应调整... 针对时间弹性带(TEB)算法在复杂环境下出现加速度变化率突变、控制指令不平滑的问题,提出改进的TEB算法.在原始TEB算法基础上引入加加速度(jerk)约束来平滑速度和加速度曲线,避免机器人在运动过程中发生震荡、抖动现象.采用自适应调整弹性带节点数量的方法来自适应调整插值点,提高机器人移动过程中的安全稳定性.为了验证改进TEB算法的有效性,选取远距离长狭窄走廊环境和多转弯包含反向停车环境对APF算法、DWA算法、传统TEB算法和改进TEB算法进行仿真对比实验.结果表明,改进TEB算法能生成更平滑路径.在走廊环境中,其线速度方差、平均角速度、角速度方差分别较传统TEB降低了16.67%、7.38%、12.84%;在多转弯环境中,则分别降低了8.61%、4.34%、8.58%,速度与角速度更加平滑.另外,在真实实验环境下验证了算法的有效性. 展开更多
关键词 路径规划 TEB算法 移动机器人 动态避障 加加速度约束
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基于改进LOAM算法的煤矿机器人建图与导航研究 认领 引用
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作者 韩培强 冯智愚 +3 位作者 徐永刚 李仁飞 王海 姚诗雨 《煤矿安全》 CAS 北大核心 2026年第4期254-264,共11页
为满足煤矿井下复杂环境下机器人巡检高精度建图与安全导航需求,解决传统算法在井下适应性、抗干扰及路径规划协同性不足的问题,开展了基于改进激光雷达测距和测绘(Lidar Odometry and Mapping,LOAM)算法的煤矿机器人建图与导航研究。... 为满足煤矿井下复杂环境下机器人巡检高精度建图与安全导航需求,解决传统算法在井下适应性、抗干扰及路径规划协同性不足的问题,开展了基于改进激光雷达测距和测绘(Lidar Odometry and Mapping,LOAM)算法的煤矿机器人建图与导航研究。在环境地图模型构建方面,基于SLAM(Simultaneous Localization and Mapping)框架,将激光雷达采集的点云数据转换为栅格地图;针对煤矿井下粉尘干扰,引入了基于高斯概率模型的动态滤波方法,通过计算测量点有效概率剔除低概率无效点,阈值依据粉尘浓度统计特征自动调整;在特征点提取环节,融合了几何特征与纹理特征,通过计算点云邻域灰度变化梯度补充特征描述子维度,提高特征点匹配精度与地图构建质量。路径规划方面,基于改进A*算法,采用动态权重机制,根据环境障碍物密度动态调整评估函数权重,优化全局路径规划;采用动态窗口法(Dynamic Window Approach,DWA)进行局部路径规划,新增轨迹曲率惩罚项,抑制机器人急转运动;两者融合后的路径规划融合算法实现了分层式导航。仿真试验表明,改进LOAM算法地图构建绝对误差控制在-0.053~0.035 m,相对误差≤2.65%,在不同粉尘浓度环境下,运行时间和最大相对误差均优于对比算法。路径规划方面与改进蝙蝠算法、改进快速扩展随机树算法进行对比,所提算法运行时间约2 s,规划路径长度较短,避障成功率最高达98.8%。真实煤矿环境测试中,在山西某煤矿井下2000 m巷道,连续运行8 h构建500 m巷道地图,绝对误差范围收窄至-0.042~0.028 m,相对误差最大值3.2%,平均运行时间1.8 s,避障成功率为96.7%。改进LOAM算法及路径规划融合算法能够提升煤矿机器人在复杂井下环境的建图精度与导航效率。 展开更多
关键词 煤矿机器人 SLAM建图算法 LOAM算法 环境地图 路径规划 导航避障
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基于GeoSOT-3D网格的改进A*算法低空路径规划 认领 引用
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作者 周文 杨丽娟 +2 位作者 周新鹤 高思岩 邹伟林 《测绘通报》 CSCD 北大核心 2026年第4期35-40,59,共6页
低空路径规划是保障低空经济安全高效发展的核心环节,常规A*算法在三维低空环境中存在搜索效率低、路径安全性不足等问题。为解决上述难题,本文提出一种融合GeoSOT-3D网格建模的改进A*算法,用于低空路径规划。该算法基于GeoSOT-3D网格... 低空路径规划是保障低空经济安全高效发展的核心环节,常规A*算法在三维低空环境中存在搜索效率低、路径安全性不足等问题。为解决上述难题,本文提出一种融合GeoSOT-3D网格建模的改进A*算法,用于低空路径规划。该算法基于GeoSOT-3D网格构建低空三维环境模型,引入了7邻域扩展搜索策略、融入安全避障机制,并采用Catmull-Rom样条曲线对结果路径进行平滑优化。通过3组仿真试验对比,结果表明,改进A*算法在19、20、21级GeoSOT-3D网格环境中,平均搜索节点个数降低83%以上;平均耗时相较于A*算法降低约17%~26%,相较于Theta*算法降低约1%~12%。在兼顾路径安全性与平滑性的同时,改进算法提升了路径规划效率。 展开更多
关键词 GeoSOT-3D网格 A*算法 路径规划 节点扩展 安全避障
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面向复杂煤矿场景的巡检机器人即时定位与地图构建技术研究 认领 引用
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作者 杨文博 张增誉 +10 位作者 聂伟雄 陈湘源 杨宏飞 郝永 张增荣 李成 贺宇 薛挺 郭清华 周德胜 张华 《化工自动化及仪表》 CAS 2026年第3期403-409,共7页
针对煤矿环境人工巡检效率低、覆盖面小的问题,提出一种面向复杂煤矿场景的巡检机器人即时定位与地图构建(SLAM)技术。该技术以二维栅格地图为框架、三维点云地图补充细节;定位环节采用自适应蒙特卡洛定位算法实现机器人精准位姿估计,... 针对煤矿环境人工巡检效率低、覆盖面小的问题,提出一种面向复杂煤矿场景的巡检机器人即时定位与地图构建(SLAM)技术。该技术以二维栅格地图为框架、三维点云地图补充细节;定位环节采用自适应蒙特卡洛定位算法实现机器人精准位姿估计,规划环节引入改进A*算法进行全局路径规划,并结合时间弹性带算法优化局部规划。实验结果表明,所提定位算法在测量定位中最大误差与最小误差分别为1.10 m与0.02 m;在复杂定位偏移误差测试中,定位算法定位偏移误差控制在0.21 m内;在动态障碍规划中,规划算法最大偏差为1.2 m。 展开更多
关键词 巡检机器人 煤矿场景 SLAM A*算法 路径规划 避障
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虚拟编队驱动的多机悬吊系统时空协同避障 认领 引用
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作者 赵祥堂 吕斌 +2 位作者 赵志刚 苏程 孟佳东 《计算机工程与应用》 EI CSCD 北大核心 2026年第10期401-410,共10页
针对吊机末端驱动型悬吊系统多机运动时空一致性缺失与复杂环境避障的双重工程难题,提出虚拟编队驱动的时空协同避障方法。构建时间-空间双维度协同模型,将吊机末端空间位置约束与时间同步约束纳入统一框架;建立领导者-跟随者架构的虚... 针对吊机末端驱动型悬吊系统多机运动时空一致性缺失与复杂环境避障的双重工程难题,提出虚拟编队驱动的时空协同避障方法。构建时间-空间双维度协同模型,将吊机末端空间位置约束与时间同步约束纳入统一框架;建立领导者-跟随者架构的虚拟编队模型,提出时空并行协同策略(时间维度优化动作时序,空间维度规划编队整体避障轨迹);设计基于稳定蜣螂优化算法(stable dung beetle optimizer,SDBO)的避障规划方案,通过反向学习、正弦-余弦策略等改进策略提升算法全局搜索能力,并且引入环境复杂度自适应切换机制增强避障方法的动态适应性。通过仿真与实体实验验证该方法可实现复杂环境下的无碰撞轨迹规划,同时保证多机运动的同步性与协调性。研究结果为力位协同避障提供了吊机末端驱动维度的技术基础。 展开更多
关键词 悬吊系统 避障规划 时空协同 虚拟编队 稳定蜣螂优化(SDBO)算法 环境复杂度
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