scholarly journals Integrating User to Minimize Assembly Path Planning Time in PLM

2013 ◽  
pp. 471-480 ◽  
Author(s):  
Yu Yan ◽  
Emilie Poirson ◽  
Fouad Bennis
Keyword(s):  
Path Planning ◽  
Planning Time

Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation

2011 ◽  
Vol 142 ◽  
pp. 12-15
Author(s):  
Ping Feng
Keyword(s):  
Path Planning ◽  
Search Algorithm ◽  
Traffic Condition ◽  
Planning Time ◽  
Dynamic Path Planning ◽  
Short Period ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm ◽  
Chaos Genetic Algorithm

The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.

scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 333
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the rapidly exploring random tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

scholarly journals An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation

2021 ◽  
Author(s):  
Jin-Gu Kang ◽  
Yong-Sik Choi ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Interpolation Method ◽  
Optimal Path ◽  
Random Tree ◽  
Interpolation Process ◽  
Robot Path Planning ◽  
Planning Time ◽  
Enhancement Method ◽  
Robot Path

To solve the problem that sampling-based Rapidly-exploring Random Tree (RRT) method is difficult to guarantee optimality. This paper proposed the Post Triangular Processing of Midpoint Interpolation method minimized the planning time and shorter path length of the sampling-based algorithm. The proposed Post Triangular Processing of Midpoint Interpolation method makes a closer to the optimal path and somewhat solves the sharp path problem through the interpolation process. The experiments were conducted to verify the performance of the proposed method. Applying the method proposed in this paper to the RRT algorithm increases the efficiency of optimization compared to the planning time.

scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

2020 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the Rapidly exploring Random Tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

scholarly journals Path Planning of Mobile Robots in Warehouse Logistics Relying on Computer Multimedia 3D Reconstruction Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yan Sun
Keyword(s):  
Path Planning ◽  
3D Reconstruction ◽  
Optimal Solution ◽  
Planning Problem ◽  
Practical Application ◽  
Global Optimal Solution ◽  
Planning Time ◽  
Movement Path ◽  
Starting Point ◽  
Global Optimal

Because traditional methods are difficult to solve the problems related to the path planning of logistics robots, this study proposes a method of using computer multimedia 3D reconstruction technology to realize the path planning of warehouse logistics robots. Without fully considering the accurate movement path between points, according to the warehouse logistics robot, it is judged whether the starting point is at the exit. The planning problem of the movement path is converted into a TSP problem and a TS-TSP problem. Finally, the analysis of experimental results shows that the method proposed in this study converges faster than traditional algorithms and can quickly obtain the global optimal solution. At the same time, the warehousing logistics robot requires less path planning time and has strong practical application.

scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

2020 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the Rapidly exploring Random Tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

scholarly journals Path Planning and Collision Avoidance in Unknown Environments for USVs Based on an Improved D* Lite

2021 ◽  
Vol 11 (17) ◽  
pp. 7863
Author(s):  
Xiaohui Zhu ◽  
Bin Yan ◽  
Yong Yue
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Search Time ◽  
Priority Queue ◽  
Complex Environments ◽  
Safe Distance ◽  
Search Range ◽  
Planning Time ◽  
Unknown Environments

Path planning and collision avoidance during autonomous navigation in unknown environments is a crucial issue for unmanned surface vehicles (USVs). This paper improves the traditional D* Lite algorithm and achieves multi-goal path planning and collision avoidance for USVs in unknown and complex environments. By expanding the adjacent search range and setting a safe distance for USVs, we solve the issue of limited steering maneuverability in USVs with fewer DOF during autonomous navigation. We propose an approach to optimize the planned path during navigation by comparing the estimated distance with the actual distance between the current waypoint and the goal waypoint. A minimum binary heap is used to optimize the priority queue of the D* Lite and significantly reduce the path search time. Simulation results show that the improved D * Lite can significantly reduce the path planning time, optimize the planned path and solve the issue of limited steering maneuverability in USVs. We apply the algorithm to a real USV for further tests. Experimental results show that the USV can plan an optimized path while avoiding both static and dynamic obstacles in complex environments with a safe distance during autonomous navigation.

Strategies for Speeding Up Manipulator Path Planning to Find High Quality Paths in Cluttered Environments

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Pradeep Rajendran ◽  
Shantanu Thakar ◽  
Prahar M. Bhatt ◽  
Ariyan M. Kabir ◽  
Satyandra K. Gupta
Keyword(s):  
Path Planning ◽  
Failure Rate ◽  
Search Space ◽  
Tree Search ◽  
High Quality ◽  
Planning Time ◽  
Cluttered Environments ◽  
Manufacturing Applications ◽  
Point To Point ◽  
Path Quality

Abstract In many manufacturing applications, robotic manipulators need to operate in cluttered environments. Quickly finding high-quality paths is very important in applications that require high part fix and frequent setup changes. This paper presents a point-to-point path planning framework for manipulators operating in cluttered environments. It uses a bi-directional tree-search to find path and facilitates finding a balance between path quality and planning time. The framework dynamically switches between search strategies based on the search progress to produce high-quality paths quickly. This paper three main contributions. First, we extend a previously developed sampling-based modular tree-search. Specifically, we present a strategy that can sample effectively in challenging regions of the search-space by using local approximations of the configuration space. Second, we add new strategies and scheduling logic that decreases the failure rate as well as the planning time compared to the prior work. We also present an inter-tree connection strategy that adapts to collision information gathered over time. We introduce a scheduling rule that regulates the exploitation of focusing hints derived from the workspace obstacles. Third, we present theoretical reasoning behind strategy switching and how it can help decrease planning times and increase path quality. Together, these new features the reduce average failure rate by a factor of 4 and improve the average planning time by 22% over the previous work.

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