This paper presents a study on enhancing the efficiency of underwater gravity matching navigation path planning in a three-dimensional environment. Firstly, to address the challenges of the computational complexity and prolonged calculation times ass...
In this paper, we present a novel three-dimensional spatial path planning algorithm based on the Vector Field Histogram* (VFH*) approach, specifically tailored for underwater robotics applications. Our method leverages the strengths of VFH* in obstac...
Unmanned aerial vehicles (UAVs) provide efficient and flexible means for maritime emergency rescue, with path planning being a critical technology in this context. Most existing unmanned device research focuses on land-based path planning in two-dime...
Path planning techniques are of major importance for the motion of autonomous systems. In addition, the chosen path, safety, and computational burden are essential for ensuring the successful application of such strategies in the presence of obstacle...
With the rapid expansion of agricultural e-commerce in China, inefficient cloud warehouse consolidation and high environmental costs have hindered the sustainability of supply chains. To address the challenges of low vehicle loading rates and high ca...
Autonomous underwater vehicles (AUVs) operating near the seabed must maintain localization reliability while satisfying maneuverability and bottom-clearance constraints. This study proposes a three-dimensional near-seabed path-planning framework inte...
Coordinated multi-unmanned aerial vehicles (UAVs) planning requires the joint consideration of spatial paths, flight speeds, arrival times, and separation constraints. This study develops an improved whale optimization algorithm (IWOA) for offline pa...
This paper proposes an improved standard particle swarm optimization 2011 for autonomous underwater vehicles (AUVs). A mutation operator with a threshold is introduced to solve the problem of particles falling into the local extreme, and a nonlinear...
Urban low-altitude unmanned aerial vehicle (UAV) planning is inherently spatiotemporal because route feasibility and cost depend on segment arrival times. Search-stage surrogates may therefore favor paths that fail execution-level checks as moving ob...
Complex three-dimensional path planning requires a planner to generate collision-free, short, and smooth paths within limited computation time, but traditional RRT-based methods often suffer from unguided sampling, repeated expansion failures in dens...
Path planning is an intertemporal problem in the robotics industry. Over the years, several algorithms have been proposed to solve it, but weaknesses are constantly identified by researchers, especially in creating an optimal path in a three-dimensio...
An effective path-planning algorithm in three-dimensional (3D) environments based on a geometric approach for redundant/hyper-redundant manipulators are presented in this paper. The method works within confined spaces cluttered with obstacles in real...
Hilly terrain farmland has diverse landforms, small fields, and unevenness. Thus, realizing farmland operation mechanization and automation is a difficult problem and has become one of the current research directions to implement agricultural mechani...
To address the challenges of high computational complexity, inferior path performance, and the balance between path quality and efficiency in traditional 3D omnidirectional path planning algorithms for UAVs, this study proposes an innovative precisio...
Path planning is crucial for autonomous underwater vehicles (AUVs) and plays a vital role in ocean engineering. To improve the search efficiency and accuracy, this study proposed a three-dimensional path-planning method for AUVs based on the interval...
Path planning is a challenging, computationally complex optimization task in high-dimensional scenarios. The metaheuristic algorithm provides an excellent solution to this problem. The dung beetle optimizer (DBO) is a recently developed metaheuristic...
Three-dimensional path planning is instrumental in path decision making and obstacle avoidance for deep-sea mining vehicles (DSMV). However, conventional particle swarm algorithms have been prone to trapping in local optima and have slow convergence...
The multi-strategy optimized dream optimization algorithm (MSDOA) is proposed to address the challenges of inadequate search capability, slow convergence, and susceptibility to local optima in intelligent optimization algorithms applied to UAV three-...
Path planning, which is needed to obtain collision-free optimal paths in complex environments, is one key step within unmanned aerial vehicle (UAV) systems with various applications, such as agricultural production, target tracking, and environmental...
The rapid advancement of unmanned aerial vehicles (UAVs) has greatly increased the application of various swarm intelligence algorithms in UAV path planning. To address the potential issues with the dung beetle optimizer (DBO) in UAV trajectory plann...
The complexity of three-dimensional (3D) dynamic urban environments poses new challenges to emerging unmanned aerial vehicle (UAV) path planning, especially in dense buildings, dynamic obstacles, and multi-UAV collaboration. This paper reviews mainst...
With the rapid development of the big data era, Unmanned Aerial Vehicles (UAVs) are being increasingly adopted for various complex environments. This has imposed new requirements for UAV path planning. How to efficiently organize, manage, and express...
To address multi-UAV cooperative path planning in complex three-dimensional dynamic environments, this paper proposes an Improved Spider Wasp Optimization (ISWO) algorithm to overcome the original SWO’s shortcomings: poor population diversity,...
This study addresses the flight-path planning problem for multirotor aerial vehicles (AVs). We consider the specific features and requirements of real-time flight-path planning and develop a rapidly-exploring random tree (RRT) algorithm to determine...
This paper presents an efficient method for securing navigation performance by suppressing divergence risk of LiDAR SLAM through a newly proposed geometric observability analysis in a three-dimensional point cloud map. For this, observability charact...
Sampling-based algorithms are pivotal for high-dimensional UAV path planning, especially in 3D urban environments. The Rapidly-Exploring Random Tree (RRT) suffers from inadequate sampling methods and a single, fixed sampling policy, which lead to elo...
UAV-based visual inspection has become an effective approach for acquiring surface information from three-dimensional building structures. However, existing coverage path planning methods usually treat viewpoint planning and path sequencing as two se...
In complex three-dimensional airspace, UAV trajectory planning is subject to stringent real-time constraints and must rapidly generate collision-free, near-optimal and curvature-continuous feasible flight paths within a limited computational window....
The cultivation model for spindle-shaped apple trees is widely used in modern standard apple orchards worldwide and represents the direction of modern apple industry development. However, without an effective obstacle avoidance path, the robotic arm...
Metaheuristic methods for three-dimensional (3D) unmanned aerial vehicle (UAV) path planning often suffer from premature convergence and reduced accuracy in complex high-dimensional spaces, in which waypoint-based decision variables exhibit structure...
To improve the reliability and path quality of three-dimensional UAV path planning in complex mountainous environments, this paper proposes an Adaptive Elite Differential Gold Rush Optimizer (AEDGRO). The main novelty of AEDGRO lies in the coordinate...
In complex environments, three-dimensional path planning for agricultural UAVs involves the comprehensive consideration of multiple factors, including obstacle avoidance, path optimization, and computational efficiency, which significantly complicate...
With the rapid development of precision agriculture technology worldwide, plant protection unmanned aerial vehicles (UAVs) have been widely applied in the prevention and control of agricultural pests and diseases due to their advantages such as unres...
Unmanned helicopter (UH) is often utilized for raid missions because it can evade radar detection by flying at ultra-low altitudes. Path planning is the key technology to realizing the autonomous action of UH. On the one hand, the dynamically changin...
Autonomous vehicles play a crucial role in three-dimensional transportation systems and have been extensively investigated and implemented in mining and other fields. However, the diverse and intricate terrain characteristics present challenges to ve...
Three-dimensional UAV path planning is crucial in practical applications. However, existing metaheuristic algorithms often suffer from slow convergence and susceptibility to becoming trapped in local optima. To address these limitations, this paper p...
Unmanned Aerial Vehicles (UAVs) have become a key technology in precision agriculture, enabling efficient monitoring, inspection, and targeted interventions. However, effective UAV path planning in such environments requires the generation of safe, e...
To address slow convergence, local optimum stagnation, and multi-objective imbalance problems for unmanned aerial vehicle (UAV) three-dimensional (3D) path planning in complex obstacle environments, an improved adaptive two-stage pigeon swarm optimiz...
The current challenge in drone swarm technology is three-dimensional path planning and adaptive formation changes. The traditional A* algorithm has limitations, such as low efficiency, difficulty in handling obstacles, and numerous turning points, wh...
Snake-like robots, characterized by their high flexibility and multi-joint structure, exhibit exceptional adaptability to complex terrains such as snowfields, jungles, deserts, and underwater environments. Their ability to navigate narrow spaces and...
Computer vision-based path planning can play a crucial role in numerous technologically driven smart applications. Although various path planning methods have been proposed, limitations, such as unreliable three-dimensional (3D) localization of objec...
Remotely operated vehicles (ROVs) equipped with multibeam forward-looking sonar are widely used for underwater object search in environments where visibility is limited. Ensuring complete three-dimensional (3D) scan coverage within a bounded mission...
Planning collision-free paths for unmanned aerial vehicles in cluttered three-dimensional environments requires balancing path length, smoothness, and consistency across repeated queries. However, existing bidirectional RRT* planners generally do not...
Three-dimensional path planning in emergency logistics is a complex optimization problem, particularly challenging because it requires considering conflicting objectives such as flight time, energy consumption, and obstacle avoidance. Unlike most urb...
The challenging terrain and deep ravines that characterize mountainous regions often result in slower path planning and suboptimal flight paths for unmanned aerial vehicles (UAVs) when traditional meta-heuristic optimization algorithms are employed....
The path planning of unmanned aerial vehicles (UAVs) is crucial in UAV search and rescue operations to ensure efficient and safe search activities. However, most existing path planning algorithms are not suitable for post-disaster mountain rescue mis...
Aiming at the cooperative path-planning problem of multiple autonomous underwater vehicles in underwater three-dimensional terrain and dynamic ocean current environments, a hybrid algorithm based on the Improved Multi-Objective Particle Swarm Optimiz...
In order to solve the problem of how to perform path planning for AUVs with multiple obstacles in a 3D underwater environment, this paper proposes a six-direction search scheme based on neural networks. In known environments with stationary obstacles...
This paper proposes an Improved Spider Wasp Optimizer (ISWO) to address inaccuracies in calculating the population
This study presents an improved UAV-based structure inspection method that integrates advanced 3D modeling and optimized path planning with obstacle avoidance. The system uses Meshroom, an open-source software, to combine multiple sets of 3D point cl...
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