scholarly journals Hybrid Assembly Path Planning for Complex Products by Reusing a Priori Data

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 395
Author(s):  
Guodong Yi ◽  
Chuanyuan Zhou ◽  
Yanpeng Cao ◽  
Hangjian Hu
Keyword(s):  
Path Planning ◽  
A Priori ◽  
Planning Method ◽  
Hybrid Assembly ◽  
Planning Stage ◽  
Complex Products ◽  
Success Ratio ◽  
Starting Point ◽  
The Difference ◽  
Window Approach

Assembly path planning (APP) for complex products is challenging due to the large number of parts and intricate coupling requirements. A hybrid assembly path planning method is proposed herein that reuses a priori paths to improve the efficiency and success ratio. The assembly path is initially segmented to improve its reusability. Subsequently, the planned assembly paths are employed as a priori paths to establish an a priori tree, which is expanded according to the bounding sphere of the part to create the a priori space for path searching. Three rapidly exploring random tree (RRT)-based algorithms are studied for path planning based on a priori path reuse. The RRT* algorithm establishes the new path exploration tree in the early planning stage when there is no a priori path to reuse. The static RRT* (S-RRT*) and dynamic RRT* (D-RRT*) algorithms form the connection between the exploration tree and the a priori tree with a pair of connection points after the extension of the exploration tree to a priori space. The difference between the two algorithms is that the S-RRT* algorithm directly reuses an a priori path and obtains a new path through static backtracking from the endpoint to the starting point. However, the D-RRT* algorithm further extends the exploration tree via the dynamic window approach to avoid collision between an a priori path and obstacles. The algorithm subsequently obtains a new path through dynamic and non-continuous backtracking from the endpoint to the starting point. A hybrid process combining the RRT*, S-RRT*, and D-RRT* algorithms is designed to plan the assembly path for complex products in several cases. The performances of these algorithms are compared, and simulations indicate that the S-RRT* and D-RRT* algorithms are significantly superior to the RRT* algorithm in terms of the efficiency and success ratio of APP. Therefore, hybrid path planning combining the three algorithms is helpful to improving the assembly path planning of complex products.

Local Path Planning for Dual-Arm Mobile Robot Shuttling within Truss

2012 ◽  
Vol 452-453 ◽  
pp. 1220-1224
Author(s):  
Wei Guo Wu ◽  
Peng Wu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Planning Method ◽  
Planning Stage ◽  
Probabilistic Roadmaps ◽  
Local Path Planning ◽  
Smooth Path ◽  
Local Path ◽  
Two Stages ◽  
Dual Arm

A new local path planning method for dual-arm mobile robot shuttling within the truss is presented. Like the probabilistic roadmaps method, this method proceeds in two stages: preprocessing stage and path planning stage. In preprocessing stage, the workspace is divided into a set of non-overlapping cubical cells. The nodes in the free workspace are stored in a matrix. In path planning stage, three query strategies are adopted to search the path from start point to goal point. Take use of vertex query strategy, the smooth path can be acquired in a fraction of a second. The algorithm is simple, and is applicable to any static environment with convex obstacles.

scholarly journals Rollover-Free Path Planning for Off-Road Autonomous Driving

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 614
Author(s):  
Xingyu Li ◽  
Bo Tang ◽  
John Ball ◽  
Matthew Doude ◽  
Daniel W. Carruth
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Autonomous Driving ◽  
Planning Method ◽  
Local Planning ◽  
Planning Stage ◽  
Local Path Planning ◽  
Global Route ◽  
Local Path ◽  
Global Planning

Perception, planning, and control are three enabling technologies to achieve autonomy in autonomous driving. In particular, planning provides vehicles with a safe and collision-free path towards their destinations, accounting for vehicle dynamics, maneuvering capabilities in the presence of obstacles, traffic rules, and road boundaries. Existing path planning algorithms can be divided into two stages: global planning and local planning. In the global planning stage, global routes and the vehicle states are determined from a digital map and the localization system. In the local planning stage, a local path can be achieved based on a global route and surrounding information obtained from sensors such as cameras and LiDARs. In this paper, we present a new local path planning method, which incorporates a vehicle’s time-to-rollover model for off-road autonomous driving on different road profiles for a given predefined global route. The proposed local path planning algorithm uses a 3D occupancy grid and generates a series of 3D path candidates in the s-p coordinate system. The optimal path is then selected considering the total cost of safety, including obstacle avoidance, vehicle rollover prevention, and comfortability in terms of path smoothness and continuity with road unevenness. The simulation results demonstrate the effectiveness of the proposed path planning method for various types of roads, indicating its wide practical applications to off-road autonomous driving.

Path planning of mobile robot with PSO-based APF and fuzzy-based DWA subject to moving obstacles

2021 ◽  
pp. 014233122110247
Author(s):  
Zenan Lin ◽  
Ming Yue ◽  
Guangyi Chen ◽  
Jianzhong Sun
Keyword(s):  
Path Planning ◽  
Risk Index ◽  
Planning Method ◽  
Collision Risk ◽  
Fitness Functions ◽  
Moving Obstacles ◽  
Control Scheme ◽  
Local Path ◽  
Window Approach ◽  
Global And Local

This paper proposes a two-layer path-planning method, where an optimized artificial potential field (APF) method and an improved dynamic window approach (DWA) are used at the global and local layer, respectively. This method enables the robot to plan a better path under a multi-obstacle environment while avoiding the moving obstacles effectively. For the part of global path planning, a new repulsive field is proposed based on the APF method. The length and smoothness of the global path are taken as fitness functions of particle swarm optimization (PSO) to obtain the obstacle influence range, the coefficients of gravitation and repulsion in APF. At the level of local path planning, on the basis of DWA, a fuzzy control scheme is adopted to evaluate the danger level of moving obstacles via collision risk index and relative distance. In brief, compared with existing methods, the robot can reasonably plan a shorter and smoother path with the aid of PSO-based APF, meanwhile quickly react to the moving obstacles and avoid them by fuzzy-based DWA. Finally, a static multi-obstacle environment and two dynamic scenarios with moving obstacles are simulated to verify the effectiveness of the proposed path-planning method.

scholarly journals Global Dynamic Path Planning Fusion Algorithm Combining Jump-A* Algorithm and Dynamic Window Approach

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 19632-19638
Author(s):  
Lisang Liu ◽  
Jinxin Yao ◽  
Dongwei He ◽  
Jian Chen ◽  
Jing Huang ◽  
...  
Keyword(s):  
Path Planning ◽  
A Algorithm ◽  
Fusion Algorithm ◽  
Global Dynamic ◽  
Dynamic Path Planning ◽  
Dynamic Path ◽  
Window Approach

scholarly journals Finite Pure Plane Strain Bending of Inhomogeneous Anisotropic Sheets

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 145
Author(s):  
Sergei Alexandrov ◽  
Elena Lyamina ◽  
Yeong-Maw Hwang
Keyword(s):  
Plane Strain ◽  
Yield Criterion ◽  
Large Strains ◽  
Rigid Plastic ◽  
Plastic Properties ◽  
Elastic Plastic ◽  
Starting Point ◽  
The Difference ◽  
Inside Radius ◽  
Elastic Unloading

The present paper concerns the general solution for finite plane strain pure bending of incompressible, orthotropic sheets. In contrast to available solutions, the new solution is valid for inhomogeneous distributions of plastic properties. The solution is semi-analytic. A numerical treatment is only necessary for solving transcendent equations and evaluating ordinary integrals. The solution’s starting point is a transformation between Eulerian and Lagrangian coordinates that is valid for a wide class of constitutive equations. The symmetric distribution relative to the center line of the sheet is separately treated where it is advantageous. It is shown that this type of symmetry simplifies the solution. Hill’s quadratic yield criterion is adopted. Both elastic/plastic and rigid/plastic solutions are derived. Elastic unloading is also considered, and it is shown that reverse plastic yielding occurs at a relatively large inside radius. An illustrative example uses real experimental data. The distribution of plastic properties is symmetric in this example. It is shown that the difference between the elastic/plastic and rigid/plastic solutions is negligible, except at the very beginning of the process. However, the rigid/plastic solution is much simpler and, therefore, can be recommended for practical use at large strains, including calculating the residual stresses.

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