Investigation of Branch Accessibility with a Robotic Pruner for Pruning Apple Trees

2021 ◽  
Vol 64 (5) ◽  
pp. 1459-1474
Author(s):  
Azlan Zahid ◽  
Long He ◽  
Daeun Choi ◽  
James Schupp ◽  
Paul Heinemann
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Path Length ◽  
Computation Time ◽  
Tree Canopy ◽  
Random Tree ◽  
Target Point ◽  
List Type ◽  
Apple Trees ◽  
End Effector

HighlightsA branch accessibility simulation was performed for robotic pruning of apple trees.A virtual tree environment was established using a kinematic manipulator model and an obstacle model.Rapidly-exploring random tree (RRT) was combined with smoothing and optimization for improved path planning.Effects on RRT path planning of the approach angle of the end-effector and cutter orientation at the target were studied.Abstract. Robotic pruning is a potential solution to reduce orchard labor and associated costs. Collision-free path planning of the manipulator is essential for successful robotic pruning. This simulation study investigated the collision-free branch accessibility of a six rotational (6R) degrees of freedom (DoF) robotic manipulator with a shear cutter end-effector. A virtual environment with a simplified tall spindle tree canopy was established in MATLAB. An obstacle-avoidance algorithm, rapidly-exploring random tree (RRT), was implemented for establishing collision-free paths to reach the target pruning points. In addition, path smoothing and optimization algorithms were used to reduce the path length and calculate the optimized path. Two series of simulations were conducted: (1) performance and comparison of the RRT algorithm with and without smoothing and optimization, and (2) performance of collision-free path planning considering different approach poses of the end-effector relative to the target branch. The simulations showed that the RRT algorithm successfully avoided obstacles and allowed the manipulator to reach the target point with 23 s average path finding time. The RRT path length was reduced by about 28% with smoothing and by 25% with optimization. The RRT smoothing algorithm generated the shortest path lengths but required about 1 to 3 s of additional computation time. The lowest coefficient of variation and standard deviation values were found for the optimization method, which confirmed the repeatability of the method. Considering the different end-effector approach poses, the simulations suggested that successfully finding a collision-free path was possible for branches with no existing path using the ideal (perpendicular cutter) approach pose. This study provides a foundation for future work on the development of robotic pruning systems. Keywords: Agricultural robotics, Collision-free path, Manipulator, Path planning, Robotic pruning, Virtual tree environment.

scholarly journals Mobile Robot Path Planning Based on a Generalized Wavefront Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Sifan Wu ◽  
Yu Du ◽  
Yonghua Zhang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Path Length ◽  
Computation Time ◽  
Target Point ◽  
Multiple Target ◽  
Robot Path Planning ◽  
Practical Applications ◽  
Real Time Applications ◽  
Robot Path

This study develops a generalized wavefront algorithm for conducting mobile robot path planning. The algorithm combines multiple target point sets, multilevel grid costs, logarithmic expansion around obstacles, and subsequent path optimization. The planning performances obtained with the proposed algorithm, the A∗ algorithm, and the rapidly exploring random tree (RRT) algorithm optimized using a Bézier curve are compared using simulations with different grid map environments comprising different numbers of obstacles with varying shapes. The results demonstrate that the generalized wavefront algorithm generates smooth and safe paths around obstacles that meet the required kinematic conditions associated with the actual maneuverability of mobile robots and significantly reduces the planned path length compared with the results obtained with the A∗ algorithm and the optimized RRT algorithm with a computation time acceptable for real-time applications. Therefore, the generated path is not only smooth and effective but also conforms to actual robot maneuverability in practical applications.

scholarly journals Efficient robotic path planning algorithm based on artificial potential field

2021 ◽  
Vol 11 (6) ◽  
pp. 4840
Author(s):  
Elia Nadira Sabudin ◽  
Rosli Omar ◽  
Sanjoy Kumar Debnath ◽  
Muhammad Suhaimi Sulong
Keyword(s):  
Computational Complexity ◽  
Path Planning ◽  
Potential Field ◽  
Path Length ◽  
Computation Time ◽  
Cell Decomposition ◽  
Target Point ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Path Planning Algorithm

<span lang="EN-US">Path planning is crucial for a robot to be able to reach a target point safely to accomplish a given mission. In path planning, three essential criteria have to be considered namely path length, computational complexity and completeness. Among established path planning methods are voronoi diagram (VD), cell decomposition (CD), probability roadmap (PRM), visibility graph (VG) and potential field (PF). The above-mentioned methods could not fulfill all three criteria simultaneously which limits their application in optimal and real-time path planning. This paper proposes a path PF-based planning algorithm called dynamic artificial PF (DAPF). The proposed algorithm is capable of eliminating the local minima that frequently occurs in the conventional PF while fulfilling the criterion of path planning. DAPF also integrates path pruning to shorten the planned path. In order to evaluate its performance, DAPF has been simulated and compared with VG in terms of path length and computational complexity. It is found that DAPF is consistent in generating paths with low computation time in obstacle-rich environments compared to VG. The paths produced also are nearly optimal with respect to VG.</span>

scholarly journals COMPUTATIONALLY EFFICIENT PATH PLANNING ALGORITHM FOR AUTONOMOUS VEHICLE

2020 ◽  
Vol 83 (1) ◽  
pp. 133-143
Author(s):  
Sanjoy Kumar Debnath ◽  
Rosli Omar ◽  
Nor Badariyah Abdul Latip ◽  
Susama Bagchi ◽  
Elia Nadira Sabudin ◽  
...  
Keyword(s):  
Path Planning ◽  
Performance Assessment ◽  
Free Path ◽  
Path Length ◽  
Autonomous Vehicle ◽  
Computation Time ◽  
Visibility Graph ◽  
Computationally Efficient ◽  
Planning Algorithm ◽  
Path Planning Algorithm

This paper analyses an experimental path planning performance between the Iterative Equilateral Space Oriented Visibility Graph (IESOVG) and conventional Visibility Graph (VG) algorithms in terms of computation time and path length for an autonomous vehicle. IESOVG is a path planning algorithm that was proposed to overcome the limitations of VG which is slow in obstacle-rich environment. The performance assessment was done in several identical scenarios through simulation. The results showed that the proposed IESOVG algorithm was much faster in comparison to VG. In terms of path length, IESOVG was found to have almost similar performance with VG.  It was also found that IESOVG was complete as it could find a collision-free path in all scenarios.

scholarly journals Optimal Path Planning using Equilateral Spaces Oriented Visibility Graph Method

2017 ◽  
Vol 7 (6) ◽  
pp. 3046 ◽  
Author(s):  
Nor Badariyah Abdul Latip ◽  
Rosli Omar ◽  
Sanjoy Kumar Debnath
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Optimal Path ◽  
Computation Time ◽  
Visibility Graph ◽  
Target Point ◽  
Improvement Rate ◽  
Starting Point ◽  
Autonomous Cars ◽  
Planning Methods

<span>Path planning has been an important aspect in the development of autonomous cars in which path planning is used to find a collision-free path for the car to traverse from a starting point Sp to a target point Tp. The main criteria for a good path planning algorithm include the capability of producing the shortest path with a low computation time. Low computation time makes the autonomous car able to re-plan a new collision-free path to avoid accident. However, the main problem with most path planning methods is their computation time increases as the number of obstacles in the environment increases. In this paper, an algorithm based on visibility graph (VG) is proposed. In the proposed algorithm, which is called Equilateral Space Oriented Visibility Graph (ESOVG), the number of obstacles considered for path planning is reduced by introducing a space in which the obstacles lie. This means the obstacles located outside the space are ignored for path planning. From simulation, the proposed algorithm has an improvement rate of up to 90% when compared to VG. This makes the algorithm is suitable to be applied in real-time and will greatly accelerate the development of autonomous cars in the near future.</span>

Path Planning for Spheres in Three Dimensional Environments With Low Interference Index

1994 ◽  
Author(s):  
Duane W. Storti ◽  
Debasish Dutta
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Configuration Space ◽  
Local Knowledge ◽  
Three Dimensional ◽  
Target Point ◽  
Planning Problem ◽  
Spherical Object ◽  
Starting Point ◽  
Path Planning Problem

Abstract We consider the path planning problem for a spherical object moving through a three-dimensional environment composed of spherical obstacles. Given a starting point and a terminal or target point, we wish to determine a collision free path from start to target for the moving sphere. We define an interference index to count the number of configuration space obstacles whose surfaces interfere simultaneously. In this paper, we present algorithms for navigating the sphere when the interference index is ≤ 2. While a global calculation is necessary to characterize the environment as a whole, only local knowledge is needed for path construction.

Autonomous Rectilinear Motion Planning for a Spatial Robot: Path Planning for a Spatial 4R Manipulator With a Single Spherical Obstacle Inside the Workspace

1992 ◽  
Vol 114 (4) ◽  
pp. 559-563 ◽  
Author(s):  
Menq-Dar Shieh ◽  
J. Duffy
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Free Path ◽  
Efficient Algorithm ◽  
Rectilinear Motion ◽  
Robot Path Planning ◽  
End Effector ◽  
Truncated Pyramid ◽  
Robot Path

This is the first of a series of papers dealing with the path planning for a spatial 4R robot with multiple spherical obstacles inside the workspace. In this paper, a time efficient algorithm has been developed to determine a collision free path for the end effector tip of the robot with a single spherical obstacle inside the workspace. A truncated pyramid and a right circular torus are used to model the nonreachable workspaces of the end effector tip of the robot. The problem of guiding the spatial 4R manipulator while avoiding a spherical obstacle is reduced to moving a point while avoiding a truncated pyramid and/or a right circular torus inside the workspace. The point represents the tip of the end effector of the manipulator. This approach produces an efficient algorithm for determining a collision free path. The algorithm has been successfully developed and implemented in the Silicon Graphics 4D-70GT workstation to verify the results.

Path Planning for Spatial Robots With Multiple Spherical and Cylindrical Obstacles Inside the Workspace

1992 ◽  
Author(s):  
Menq-Dar Shieh ◽  
Carl Crane ◽  
Joseph Duffy
Keyword(s):  
Path Planning ◽  
Coordinate System ◽  
Inclination Angle ◽  
Cross Sections ◽  
Computation Time ◽  
End Effector

Abstract Algorithms which can rapidly generate collision free paths for the end effector tip of a spatial 4R manipulator with multiple spherical or cylindrical obstacles inside the workspace have been successfully developed. The algorithms are based on the geometry of the manipulator workspace. The problem of guiding the spatial 4R manipulator while avoiding the obstacles is reduced to that of moving a point and at the same time avoiding rectangles in a Inclination Angle Coordinate System (IACS). The complexity of the path planning is reduced from the 3D case to the 2D case in the IACS, and the speed of generating the collision free paths is improved significantly without losing the characteristics of 3D path planning. The algorithms have been successfully implemented in a Silicon Graphics 4D-70GT workstation to verify the results. The computation time for generating 10 collision free paths with 7 spherical obstacles or 10 cylindrical obstacles inside the workspace is 1 or 2 seconds. Also, the algorithms, which are designed as interactive programs, are modified to guide a spatial T3586 robot around pipes with circular cross sections.

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&rsquo;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.

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