Cosine Second Order Robot Trajectory Planning Method

2011 ◽  
Vol 80-81 ◽  
pp. 1075-1080
Author(s):  
Zong Wu Xie ◽  
Cao Li ◽  
Hong Liu
Keyword(s):  
Path Planning ◽  
Trajectory Planning ◽  
Trajectory Tracking ◽  
Joint Space ◽  
Planning Method ◽  
Robot Trajectory ◽  
Great Performance ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A new joint space trajectory planning method for the series robot is proposed. Comparing with the traditional path planning methods which can only guarantee the planned trajectory velocity or acceleration continuous, the proposed trajectory planning algorithm can also ensure the derivative of acceleration (Jerk) continuous within a limit threshold. At the end of this paper, the proposed path planning algorithm is validated of having a great performance on robot trajectory tracking.

Practical high curvature path planning algorithm in joint space

2015 ◽  
Vol 51 (6) ◽  
pp. 469-471 ◽  
Author(s):  
Raimarius Delgado ◽  
Byoung Wook Choi
Keyword(s):  
Path Planning ◽  
Joint Space ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A Bidirectional Quintuple Tree Node Expansion Algorithm for UAV Path Planning in Dynamic Environment

2013 ◽  
Vol 765-767 ◽  
pp. 413-416
Author(s):  
Jian Hong Gong ◽  
Bo Li ◽  
Xiao Guang Gao
Keyword(s):  
Path Planning ◽  
Trajectory Planning ◽  
Dynamic Environment ◽  
Security Issues ◽  
Tree Node ◽  
Search Mechanism ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Optimization Search ◽  
Uav Security

To deal with the problem of penetration trajectory planning for UAV security issues, an improved bidirectional quintuple tree node expansion algorithm is proposed. Compare to traditional quintuple tree node expansion algorithm, the proposed algorithm could reduce the number of the expanded tree node, and it makes the bidirectional quintuple tree node expansion algorithm more efficient in path planning. By combining the bidirectional quintuple tree node expansion algorithm with multi-step optimization search mechanism, a kind of real-time UAV path planning algorithm is presented.

An Efficient Path-Planning Algorithm for a Robotic Manipulator by Automatic Selection Search of Indispensable Regions in Its Configuration Space

1992 ◽  
Vol 4 (5) ◽  
pp. 378-385
Author(s):  
Hiroshi Noborio ◽  
◽  
Motohiko Watanabe ◽  
Takeshi Fujii
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Configuration Space ◽  
Robotic Manipulator ◽  
Joint Space ◽  
Practical Applications ◽  
Continuous Sequence ◽  
Angle Difference ◽  
Planning Algorithm ◽  
Path Planning Algorithm

In this paper, we propose a feasible motion planning algorithm for a robotic manipulator and its obstacles. The algorithm quickly selects a feasible sequence of collision-free motions while adaptively expanding a graph in the implicit configuration joint-space. In the configuration graph, each arc represents an angle difference of the manipulator joint; therefore, an arc sequence represents a continuous sequence of robot motions. Thus, the algorithm can execute a continuous sequence of collision-free motions. Furthermore, the algorithm expands the configuration graph only in space which is to be cluttered in the implicit configuration joint-space and which is needed to select a collision-free sequence between the initial and target positions/orientations. The algorithm maintains the configuration graph in a small size and quickly selects a collision-free sequence from the configuration graph, whose shape is to be simple enough to move the manipulator in practical applications.

scholarly journals Autonomous Robots Path Planning: An Adaptive Roadmap Approach

2013 ◽  
Vol 373-375 ◽  
pp. 246-254 ◽  
Author(s):  
Mohamed Elbanhawi ◽  
Milan Simic ◽  
Reza Jazar
Keyword(s):  
Computational Complexity ◽  
Path Planning ◽  
Autonomous Robots ◽  
Autonomous Mobile Robots ◽  
Current Position ◽  
Military Applications ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Real Time Applications ◽  
Path Planning Algorithm

Developing algorithms that allow robots to independently navigate unknown environments is a widely researched area of robotics. The potential for autonomous mobile robots use, in industrial and military applications, is boundless. Path planning entails computing a collision free path from a robots current position to a desired target. The problem of path planning for these robots remains underdeveloped. Computational complexity, path optimization and robustness are some of the issues that arise. Current algorithms do not generate general solutions for different situations and require user experience and optimization. Classical algorithms are computationally extensive. This reduces the possibility of their use in real time applications. Additionally, classical algorithms do not allow for any control over attributes of the generated path. A new roadmap path planning algorithm is proposed in this paper. This method generates waypoints, through which the robot can avoid obstacles and reach its goal. At the heart of this algorithm is a method to control the distance of the waypoints from obstacles, without increasing its computational complexity. Several simulations were run to illustrate the robustness and adaptability of this approach, compared to the most commonly used path planning methods.

An Algorithm of Non-Iso Parameters Cutting Path Planning Using Toroid Cutter

2013 ◽  
Vol 373-375 ◽  
pp. 2088-2091
Author(s):  
Quan Liang ◽  
Dong Hai Su ◽  
Jie Wang ◽  
Ye Mu Wang
Keyword(s):  
Path Planning ◽  
Trajectory Planning ◽  
Tool Path ◽  
Search Algorithm ◽  
Free Form ◽  
Processing Efficiency ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Five Axis ◽  
Cutting Path

For the problem of poor processing efficiency of iso-parameter tool path planning algorithm, this paper proposed a non iso-parameter trajectory planning algorithm. First established a mathematical model of five-axis machining toroid cutter, then analyzed the toroid cutter and machining surface partial differential geometric properties, proposed one kind of iso-scallop path search algorithm. Finally, using the above algorithm developed an application of trajectory planning for free-form surface and generated tool paths for such surface. The trajectories generated verified the algorithm is practicable.

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 Reinforcement Learning Path Planning Method with Error Estimation

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 247
Author(s):  
Feihu Zhang ◽  
Can Wang ◽  
Chensheng Cheng ◽  
Dianyu Yang ◽  
Guang Pan
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Error Estimation ◽  
Autonomous Driving ◽  
Planning Method ◽  
Robot Kinematics ◽  
Learning Path ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Accumulated Error

Path planning is often considered as an important task in autonomous driving applications. Current planning method only concerns the knowledge of robot kinematics, however, in GPS denied environments, the robot odometry sensor often causes accumulated error. To address this problem, an improved path planning algorithm is proposed based on reinforcement learning method, which also calculates the characteristics of the cumulated error during the planning procedure. The cumulative error path is calculated by the map with convex target processing, while modifying the algorithm reward and punishment parameters based on the error estimation strategy. To verify the proposed approach, simulation experiments exhibited that the algorithm effectively avoid the error drift in path planning.

Robot Obstacle Avoidance and Path Planning in Configuration Space

1993 ◽  
Author(s):  
R. W. Toogood ◽  
Chi Wong
Keyword(s):  
Path Planning ◽  
Work Environment ◽  
Free Path ◽  
Obstacle Avoidance ◽  
Configuration Space ◽  
Complex Shape ◽  
Joint Space ◽  
Simple Path ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Abstract This paper deals with the problem of planning a collision-free path for a 3 link, revolute robot among fixed obstacles within its work environment. Both the payload and the robot links are checked for collisions with the obstacles. All path planning is performed in joint or configuration space. The first part of the paper is concerned with the visualization of the complex shape of the obstacles as they appear in joint space. The second part of the paper describes and presents results of a simple path planning algorithm.

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