Research and Realization of Kth Path Planning Algorithm under Large-Scale Data Which Meets the Requirement for Repeatability

2014 ◽  
Author(s):  
Lei Zhu ◽  
Qiongxin Liu ◽  
Chunxiao Gao ◽  
Jing Wang
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Large Scale Data ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Scale Data

scholarly journals Design, path planning improvement and test of a portable massage robot on human back

2018 ◽  
Vol 15 (4) ◽  
pp. 172988141878663 ◽  
Author(s):  
Wendong Wang ◽  
Peng Zhang ◽  
Chaohong Liang ◽  
Yikai Shi
Keyword(s):  
Path Planning ◽  
Input Signal ◽  
Duty Cycle ◽  
Electromagnetic Force ◽  
Large Scale ◽  
Human Life ◽  
Electric Circuit ◽  
Coil Current ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A massage robot that helps to improve the quality of human life has attracted more interests of researchers and consumers. A portable back massage robot that is compact and space-saving was designed to be used on human back instead of a traditional large-scale structure robot. To design the massage robot, the models of electric circuit, magnetic circuit and mechanics were analyzed to achieve optimal massage force. Parameters of the massage actuator are determined based on the influence analysis of the coil current, the coil turns and the distance between the moving core and the yoke on the electromagnetic force. The massage coverage of human back, which is used to calculate the massage effect, could be improved by an excellent path planning algorithm. This article proposed an efficient full covered path planning algorithm for the designed massage robot, and the relevant algorithm models were established. Simulation results show that the coil current is much more sensitive to electromagnetic force of the moving core compared to the other two factors, and the presented path planning algorithm completes full coverage of the massage robot on the back area. The experimental platform of the massage robot was built, and the influence of the input signal duty cycle, the input signal voltage and the hardness of the massage object on the massage effect was discussed by testing the values of acceleration. The tested results show that the massage effect is best when the duty cycle is in the range of 1/8–1/2. Meanwhile, the hardness of massage parts affects the massage intensity. The consistency between the tested results of path planning and simulation verifies the feasibility of the simulation procedure and indicates that the massage robot can attain the desired massage performance and realize the planned paths.

scholarly journals Rapid global path planning algorithm for unmanned surface vehicles in large-scale and multi-island marine environments

2021 ◽  
Vol 7 ◽  
pp. e612
Author(s):  
Dong Wang ◽  
Jie Zhang ◽  
Jiucai Jin ◽  
Deqing Liu ◽  
Xingpeng Mao
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Distance Constraint ◽  
Marine Environments ◽  
Fast Marching ◽  
Unmanned Surface Vehicles ◽  
Grid Map ◽  
Global Path Planning ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A global path planning algorithm for unmanned surface vehicles (USVs) with short time requirements in large-scale and complex multi-island marine environments is proposed. The fast marching method-based path planning for USVs is performed on grid maps, resulting in a decrease in computer efficiency for larger maps. This can be mitigated by improving the algorithm process. In the proposed algorithm, path planning is performed twice in maps with different spatial resolution (SR) grids. The first path planning is performed in a low SR grid map to determine effective regions, and the second is executed in a high SR grid map to rapidly acquire the final high precision global path. In each path planning process, a modified inshore-distance-constraint fast marching square (IDC-FM2) method is applied. Based on this method, the path portions around an obstacle can be constrained within a region determined by two inshore-distance parameters. The path planning results show that the proposed algorithm can generate smooth and safe global paths wherein the portions that bypass obstacles can be flexibly modified. Compared with the path planning based on the IDC-FM2 method applied to a single grid map, this algorithm can significantly improve the calculation efficiency while maintaining the precision of the planned path.

scholarly journals Value Iteration Networks with Double Estimator for Planetary Rover Path Planning

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8418
Author(s):  
Xiang Jin ◽  
Wei Lan ◽  
Tianlin Wang ◽  
Pengyao Yu
Keyword(s):  
Path Planning ◽  
Large Scale ◽  
Computational Cost ◽  
Poor Performance ◽  
Value Iteration ◽  
Training Strategy ◽  
Large Size ◽  
Planning Algorithm ◽  
Value Estimation ◽  
Path Planning Algorithm

Path planning technology is significant for planetary rovers that perform exploration missions in unfamiliar environments. In this work, we propose a novel global path planning algorithm, based on the value iteration network (VIN), which is embedded within a differentiable planning module, built on the value iteration (VI) algorithm, and has emerged as an effective method to learn to plan. Despite the capability of learning environment dynamics and performing long-range reasoning, the VIN suffers from several limitations, including sensitivity to initialization and poor performance in large-scale domains. We introduce the double value iteration network (dVIN), which decouples action selection and value estimation in the VI module, using the weighted double estimator method to approximate the maximum expected value, instead of maximizing over the estimated action value. We have devised a simple, yet effective, two-stage training strategy for VI-based models to address the problem of high computational cost and poor performance in large-size domains. We evaluate the dVIN on planning problems in grid-world domains and realistic datasets, generated from terrain images of a moon landscape. We show that our dVIN empirically outperforms the baseline methods and generalize better to large-scale environments.

Comparison between Normal Waveform and Modified Wavefront Path Planning Algorithm for Mobile Robot

2014 ◽  
Vol 607 ◽  
pp. 778-781 ◽  
Author(s):  
Swee Ho Tang ◽  
Che Fai Yeong ◽  
Eileen Lee Ming Su
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Large Scale ◽  
Simulation Software ◽  
Robot Path Planning ◽  
Full Wave ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Grid Based ◽  
Robot Path

Mobile robot path planning is about finding a movement from one position to another without collision. The wavefront is typically used for path planning jobs and appreciated for its efficiency, but it needs full wave expansion which takes significant amount of time and process in large scale environment. This study compared wavefront algorithm and modified wavefront algorithm for mobile robots to move efficiently in a collision free grid based static environment. The algorithms are compared in regards to parameters such as execution time of the algorithm and planned path length which is carried out using Player/Stage simulation software. Results revealed that modified wavefront algorithm is a much better path planning algorithm compared to normal wavefront algorithm in static environment.

scholarly journals Research on Path Planning Algorithm for Crowd Evacuation

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1339
Author(s):  
Zhenfei Wang ◽  
Chuchu Zhang ◽  
Junfeng Wang ◽  
Zhiyun Zheng ◽  
Lun Li
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Large Scale ◽  
Path Selection ◽  
Limited Area ◽  
Evacuation Time ◽  
Planning Algorithm ◽  
Crowd Evacuation ◽  
Avoidance Strategy ◽  
Path Planning Algorithm

In recent years, crowded stampede incidents have occurred frequently, resulting in more and more serious losses. The common cause of such incidents is that when large-scale populations gather in a limited area, the population is highly unstable. In emergency situations, only when the crowd reaches the safe exit as soon as possible within a limited evacuation time to complete evacuation can the loss and casualties be effectively reduced. Therefore, the safety evacuation management of people in public places in emergencies has become a hot topic in the field of public security. Based on the analysis of the factors affecting the crowd path selection, this paper proposes an improved path-planning algorithm based on BEME (Balanced Evacuation for Multiple Exits). And pedestrian evacuation simulation is carried out in multi-exit symmetrical facilities. First, this paper optimizes the update method of the GSDL list in the BEME algorithm as the basis for evacuating pedestrians to choose an exit. Second, the collision between pedestrians is solved by defining the movement rule and collision avoidance strategy. Finally, the algorithm is compared with BEME and traditional path-planning algorithms. The results show that the algorithm can further shorten the global evacuation distance of the symmetrical evacuation scene, effectively balance the number of pedestrians at each exit and reduce the evacuation time. In addition, this improved algorithm uses a collision avoidance strategy to solve the collision and congestion problems in path planning, which helps to maximize evacuation efficiency. Whether the setting of the scene or the setting of the exit, all studies are based on symmetric implementation. This is more in line with the crowd evacuation in the real scene, making the experimental results more meaningful.

Sign in / Sign up

Export Citation Format

Share Document