In order to address the shortcomings of the traditional bidirectional RRT* algorithm, such as its high degree of randomness, low search efficiency, and the many inflection points in the planned path, we institute improvements in the following directi...
This paper proposes a solution for the cooperative obstacle avoidance path planning problem in dual manipulator arms using an improved Rapidly Exploring Random Tree (RRT) algorithm. The dual manipulator arms are categorized into a main arm and a seco...
An automotive welding unit is a modular production cell within a welding workshop that integrates industrial manipulators, welding equipment, fixtures, and control systems to perform specific welding and assembly tasks. A large number of industrial m...
Aiming at the problems of low efficiency, high energy consumption, and poor path quality during the multi-mechanism operation of bridge cranes in spatial tasks, an improved Rapidly exploring Random Tree (RRT) algorithm based on multi-strategy fusion...
In the future of automated production processes, the manipulator must be more efficient to complete certain tasks. Compared to single-arm robots, dual-arm robots have a larger workspace and stronger load capacity. Coordinated motion planning of multi...
In this paper, an improved APF-GFARRT* (artificial potential field-guided fuzzy adaptive rapidly exploring random trees) algorithm based on APF (artificial potential field) guided sampling and fuzzy adaptive expansion is proposed to solve the problem...
Percutaneous puncture has become one of the most widely used minimally invasive techniques in clinical practice due to its advantages of low trauma, quick recovery and easy operation. However, incomplete needle tip movement, tissue barriers and compl...
RRT (rapidly exploring random tree) is a sampling-based planning algorithm that has been widely used due to its simple structure and fast speed. However, the RRT algorithm has several issues such as low planning efficiency, high randomness, and poor...
Due to the complexity of the marine environment, underwater target search and interception is one of the biggest problems faced by an autonomous underwater vehicle (AUV). At present, there is quite a lot of research in terms of the two-dimensional en...
To address the limitations of the traditional rapidly exploring random tree (RRT) algorithm, including redundant exploration, limited adaptability in dense environments, insufficient obstacle clearance, and poor path smoothness, this paper proposes a...
As urban power grids grow increasingly complex and underground space resources become increasingly scarce, traditional two-dimensional cable design methods face significant challenges in spatial representation accuracy and design efficiency. This stu...
Aiming at the problems of traditional Rapidly exploring Random Tree Star (RRT*), its modified algorithms in the three-dimensional complex underwater path planning of autonomous underwater vehicles (AUVs), including sampling redundancy, simplistic exp...
Aiming at the problems of a six-degree-of-freedom robotic arm in a three-dimensional multi-obstacle space, such as low sampling efficiency and path search failure, an improved fast extended random tree (RRT*) algorithm for robotic arm path planning m...
Pruning branches of apple trees is a labor-intensive task. Pruning robots can save manpower and reduce costs. A full map of the apple orchard with collision-free paths, which is navigation planning, is essential. To improve the navigation efficiency...
The Rapidly Exploring Random Tree algorithm, renowned for its randomness, asymptotic properties, and local planning capabilities, is extensively employed in autonomous driving for path planning. Addressing issues such as pronounced randomness, low se...
In order to solve the problem of obstacle avoidance for unmanned surface vehicles (USV), based on the classic RRT algorithm and Velocity Obstacle principle, an improved RRT algorithm is proposed. For the situation of the extension direction of the pa...
Unordered parcel sorting corresponds to collision-free motion planning for manipulators within 3D unstructured obstacle-laden environments. Random poses of sorted objects impose stringent requirements on planning real-time performance and trajectory...
This paper investigates the path-planning problem of unmanned aerial vehicles (UAVs) for logistics delivery in urban environments. The impact of real-time obstacle avoidance and path smoothness on the flyability of UAVs remains a challenge in existin...
In order to improve the safety and efficiency of inspection robots for solar power plants, the Rapidly Exploring Random Tree Star (RRT*) algorithm is studied and an improved method based on an adaptive target bias and heuristic circular sampling is p...
The Rapidly-exploring Random Tree (RRT) algorithm faces issues in path planning, including low search efficiency, high randomness, and suboptimal path quality. To overcome these issues, this paper proposes an improved RRT planning algorithm based on...
In complex environments, path planning is the key for unmanned aerial vehicles (UAVs) to perform military missions autonomously. This paper proposes a novel algorithm called flight cost-based Rapidly-exploring Random Tree star (FC-RRT*) extending the...
Efficient and effective path planning can significantly enhance the task execution capabilities of UAVs in complex environments. This paper proposes an improved sampling-based path planning algorithm, Bi-APF-RRT*, which integrates an Artificial Poten...
Path planning is one of the key technologies for unmanned driving of underground intelligent vehicles. Due to the complexity of the drift environment and the vehicle structure, some improvements should be made to adapt to underground mining condition...
Autonomous valet parking technology refers to a vehicle’s use of onboard sensors and line-controlled chassis to carry out a fully automatic valet parking function, which can greatly improve the driver’s experience. This study focuses on a...
In complex obstacle environments, the RRT* algorithm, an asymptotically optimal variant of the Rapidly exploring Random Tree (RRT), and its related variants often suffer from slow generation of the initial feasible solution, unstable sampling efficie...
For the RRT* algorithm, there are problems such as greater randomness, longer time consumption, more redundant nodes, and inability to perform local obstacle avoidance when encountering unknown obstacles in the path planning process of autonomous veh...
Ship path planning is crucial for the shipping industry, especially for the development of autonomous ships. Many algorithms have been developed over the last few decades to solve the ship path planning problem. However, it is still challenging for s...
This paper proposed an improved potential rapidly exploring random tree star (P-RRT*) algorithm for unmanned aerial vehicles (UAV). The algorithm has faster expansion and convergence speeds and better path quality. Path planning is an important part...
The Rapidly-exploring Random Tree Star (RRT*) algorithm, widely utilized for path planning, faces challenges, such as slow acquisition of feasible paths and high path costs. To address this issue, this paper presents an improved algorithm based on RR...
Path planning is a fundamental challenge for autonomous robots, particularly in unstructured environments, where issues such as low search efficiency, suboptimal path quality, and local optima often arise. To address these challenges and enable a non...
In order to solve the problems of traditional RRT algorithms that are too random in planning, have low planning efficiency, and have insufficient security, this paper proposes an algorithm that fuses APF and the improved bidirectional RRT* algorithm...
To address the limitations of the standard Informed-RRT* algorithm in manipulator path planning, including low initial path search efficiency, susceptibility to local optima in complex obstacle environments, and high path redundancy, this paper propo...
It is well known that path planning has always been an important study area for intelligent ships, especially for unmanned surface vehicles (USVs). Therefore, it is necessary to study the path-planning algorithm for USVs. As one of the basic algorith...
In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human–Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the proc...
Winter jujube harvesting is traditionally labor-intensive, yet declining labor availability and rising costs necessitate robotic automation to maintain agricultural competitiveness. Path planning for robotic arms in orchards faces challenges due to t...
We present a hybrid algorithm for 3D obstacle-avoidance path planning of a six-axis robotic arm in cable inspection environments. It improves on traditional RRT, which suffers from blind sampling and low efficiency, and APF, which tends to become stu...
Aiming at the problem that the traditional rapidly exploring random tree (RRT) algorithm only considers the global path of unmanned vehicles in a static environment, which has the limitation of not being able to avoid unknown dynamic obstacles in rea...
Given that the rapidly exploring random tree algorithm (RRT) and its variants cannot efficiently solve problems of path planning of autonomous vehicles, this paper proposes a new, adaptive improved RRT algorithm. Firstly, an adaptive directional samp...
The autonomous navigation of an Unmanned Underwater Vehicle (UUV) in unknown 3D underwater environments remains a challenging task due to the presence of complex terrain, uncertain obstacles, and strict kinematic constraints. This paper proposes a no...
In response to issues such as insufficient bias in random sampling, low convergence efficiency, inadequate path search efficiency, and lack of path smoothness encountered by the traditional RRT* algorithm during path planning, an improved algorithm i...
Sampling-based path planning is widely used in autonomous navigation, but Informed-RRT* still relies mainly on geometric ellipsoidal sampling and does not explicitly evaluate local obstacle risk, which can lead to invalid expansion, redundant nodes,...
Efficient and safe path planning is the core prerequisite for realizing the autonomous crushing operation of the hydraulic crushing robotic arm in the mine chute. Foundational sampling-based algorithms, specifically standard RRT* and Informed RRT*, h...
To address the shortcomings of the original rapidly-exploring random tree (RRT) algorithm, such as long and non-smooth paths, slow convergence to the goal region, and limited adaptability in dynamic environments, this paper proposes a hybrid path pla...
The existing variants of the rapidly exploring random tree (RRT) cannot be effectively applied in local path planning of the autonomous vehicle and solve the coherence problem of paths between the front and back frames. Thus, an improved heuristic Bi...
In view of the problem that path planning and trajectory tracking are rarely solved simultaneously in the current research, which hinders their practical implementation, this paper focuses on enhancing the autonomous flight planning capability of unm...
Aiming at precisely tracking an intelligent vehicle on a desired trajectory, this paper proposes an intelligent vehicle trajectory planning and control strategy based on an improved terminal sliding mold. Firstly, the traditional RRT algorithm is imp...
At present, there is a lack of effective and usable machinery in the harvesting of aquatic vegetables. The harvesting of most aquatic vegetables such as Brasenia schreberi relies entirely on manual labor, resulting in a high labor demand and labor sh...
Water quality sampling and monitoring are fundamental to water environmental protection. The purpose of this study was to develop a water quality sampling and multi-parameter monitoring system mounted on a multi-rotor unmanned aerial vehicle (UAV). T...
Unmanned sailboats rely on wind and solar energy for long-duration marine missions, yet their navigation performance is strongly constrained by sail aerodynamics, hull hydrodynamics, and time-varying wind fields. Due to their underactuated nature and...
In view of the large randomness, redundant path nodes, and low search efficiency of RRT-connect in a complex obstacle environment, this study intends to develop a path-planning method combining RRT-connect and Informed RRT*. First, to solve the probl...
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