Trajectory Planning for a Articulated Robot

2015 ◽  
Vol 742 ◽  
pp. 576-581
Author(s):  
Kai Kai Wang ◽  
Jia Qi Li ◽  
Yuan Wei Zou ◽  
Cheng Li Wang ◽  
Liu Bo Liang
Keyword(s):  
Trajectory Planning ◽  
Reference Value ◽  
Matlab Simulation ◽  
Robot Trajectory ◽  
Starting Point ◽  
Depth Study ◽  
Planning Algorithm ◽  
Articulated Robot ◽  
Path Planning Algorithm ◽  
Destination Point

This paper focuses on the robot trajectory planning algorithm in-depth study, we propose a new path planning algorithm to ensure that the velocity and the acceleration of the starting point and the destination point are zero at the same time, and there are continuity of the intermediate points also.Give the matlab simulation waveform diagram and the algorithm at last,and this trajectory planning provides a good reference value for robot trajectory studies of future.

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.

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.

scholarly journals Development of articulated robot trajectory planning

2017 ◽  
Vol 8 (1) ◽  
pp. 52 ◽  
Author(s):  
Zhe Li ◽  
Gongfa Li ◽  
Ying Sun ◽  
Guozhang Jiang ◽  
Jianyi Kong ◽  
...  
Keyword(s):  
Trajectory Planning ◽  
Robot Trajectory ◽  
Articulated Robot ◽  
Robot Trajectory Planning

scholarly journals Development and Implementation of Spline-based Path Planning Algorithm in ROS/Gazebo Environment

2019 ◽  
Vol 18 (1) ◽  
pp. 57-84 ◽  
Author(s):  
Lavrenov Lavrenov ◽  
Evgeni Magid ◽  
Matsuno Fumitoshi ◽  
Mikhail Svinin ◽  
Jackrit Suthakorn
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Cost Function ◽  
Working Environment ◽  
Autonomous Mobile Robots ◽  
Dynamic Tuning ◽  
Starting Point ◽  
Geometric Point ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Path planning for autonomous mobile robots is an important task within robotics field. It is common to use one of the two classical approaches in path planning: a global approach when an entire map of a working environment is available for a robot or local methods, which require the robot to detect obstacles with a variety of onboard sensors as the robot traverses the environment. In our previous work, a multi-criteria spline algorithm prototype for a global path construction was developed and tested in Matlab environment. The algorithm used the Voronoi graph for computing an initial path that serves as a starting point of the iterative method. This approach allowed finding a path in all map configurations whenever the path existed. During the iterative search, a cost function with a number of different criteria and associated weights was guiding further path optimization. A potential field method was used to implement some of the criteria. This paper describes an implementation of a modified spline-based algorithm that could be used with real autonomous mobile robots. Equations of the characteristic criteria of a path optimality were further modified. The obstacle map was previously presented as intersections of a finite number of circles with various radii. However, in real world environments, obstacles’ data is a dynamically changing probability map that could be based on an occupancy grid. Moreover, the robot is no longer a geometric point. To implement the spline algorithm and further use it with real robots, the source code of the Matlab environment prototype was transferred into C++ programming language. The testing of the method and the multi criteria cost function optimality was carried out in ROS/Gazebo environment, which recently has become a standard for programming and modeling robotic devices and algorithms. The resulting spline-based path planning algorithm could be used on any real robot, which is equipped with a laser rangefinder. The algorithm operates in real time and the influence of the objective function criteria parameters are available for dynamic tuning during a robot motion.

A Proposed Trajectory Planning Algorithm for Mobile Robot Navigation Based on A* Algorithm

2020 ◽  
pp. 361-376
Author(s):  
Şahin Yıldırım ◽  
Sertaç Savaş
Keyword(s):  
Mobile Robot ◽  
Trajectory Planning ◽  
Heuristic Method ◽  
Working Environment ◽  
Mobile Robot Navigation ◽  
A Algorithm ◽  
Grid Map ◽  
Planning Approach ◽  
Planning Algorithm ◽  
Path Planning Algorithm

This chapter proposes a new trajectory planning approach by improving A* algorithm, which is a widely-used, path-planning algorithm. This algorithm is a heuristic method used in maps such as the occupancy grid map. As the resolution increases in these maps, obstacles can be defined more precisely. However, the cell/grid size must be larger than the size of the mobile robot to prevent the robot from crashing into the borders of the working environment or obstacles. The second constraint of the algorithm is that it does not provide continuous headings. In this study, an avoidance area is calculated on the map for the mobile robot to avoid collisions. Then curve-fitting methods, general polynomial and b-spline, are applied to the path calculated by traditional A* algorithm to obtain smooth rotations and continuous headings by staying faithful to the original path calculated. Performance of the proposed trajectory planning method is compared to others for different target points on the grid map by using a software developed in Labview Environment.

scholarly journals Trajectory Planning Algorithm of UAV Based on System Positioning Accuracy Constraints

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 250 ◽  
Author(s):  
Hao Zhou ◽  
Hai-Ling Xiong ◽  
Yun Liu ◽  
Nong-Die Tan ◽  
Lei Chen
Keyword(s):  
Trajectory Planning ◽  
System Structure ◽  
Improved Genetic Algorithm ◽  
A Algorithm ◽  
Positioning Accuracy ◽  
Error Corrections ◽  
Starting Point ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Accuracy Constraints

This paper describes a novel trajectory planning algorithm for an unmanned aerial vehicle (UAV) under the constraints of system positioning accuracy. Due to the limitation of the system structure, a UAV cannot accurately locate itself. Once the positioning error accumulates to a certain degree, the mission may fail. This method focuses on correcting the error during the flight process of a UAV. The improved genetic algorithm (GA) and A* algorithm are used in trajectory planning to ensure the UAV has the shortest trajectory length from the starting point to the ending point under multiple constraints and the least number of error corrections.

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.

Investigating Reduced Path Planning Strategy for Differential Wheeled Mobile Robot

Robotica ◽  
2019 ◽  
Vol 38 (2) ◽  
pp. 235-255 ◽  
Author(s):  
Raouf Fareh ◽  
Mohammed Baziyad ◽  
Mohammad H. Rahman ◽  
Tamer Rabie ◽  
Maamar Bettayeb
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Control Strategy ◽  
Wheeled Mobile Robot ◽  
Computational Time ◽  
Planning Strategy ◽  
Starting Point ◽  
Planning Algorithm ◽  
Path Efficiency ◽  
Path Planning Algorithm

SummaryThis paper presents a vision-based path planning strategy that aims to reduce the computational time required by a robot to find a feasible path from a starting point to the goal point. The proposed algorithm presents a novel strategy that can be implemented on any well-known path planning algorithm such as A*, D* and probabilistic roadmap (PRM), to improve the swiftness of these algorithms. This path planning algorithm is suitable for real-time scenarios since it reduces the computational time compared to the basis and traditional algorithms. To test the proposed path planning strategy, a tracking control strategy is implemented on a mobile platform. This control strategy consists of three major stages. The first stage deals with gathering information about the surrounding environment using vision techniques. In the second stage, a free-obstacle path is generated using the proposed reduced scheme. In the final stage, a Lyapunov kinematic tracking controller and two Artificial Neural Network (ANN) based-controllers are implemented to track the proposed path by adjusting the rotational and linear velocity of the robot. The proposed path planning strategy is tested on a Pioneer P3-DX differential wheeled mobile robot and an Xtion PRO depth camera. Experimental results prove the efficiency of the proposed path planning scheme, which was able to reduce the computational time by a large percentage which reached up to 88% of the time needed by the basis and traditional scheme, without significant adverse effect on the workability of the basis algorithm. Moreover, the proposed path planning algorithm has improved the path efficiency, in terms of the path length and trackability, challenging the traditional trade-off between swiftness and path efficiency.

scholarly journals Development of articulated robot trajectory planning

2017 ◽  
Vol 8 (1) ◽  
pp. 52
Author(s):  
Guozhang Jiang ◽  
Gongfa Li ◽  
Jianyi Kong ◽  
Ying Sun ◽  
Zhe Li ◽  
...  
Keyword(s):  
Trajectory Planning ◽  
Robot Trajectory ◽  
Articulated Robot ◽  
Robot Trajectory Planning
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