scholarly journals SBMPO: Sampling Based Model Predictive Optimization for robot trajectory planning

2021 ◽  
pp. 100159
Author(s):  
Mario Harper ◽  
Camilo Ordonez ◽  
Emmanuel Collins
Keyword(s):  
Trajectory Planning ◽  
Robot Trajectory ◽  
Robot Trajectory Planning

scholarly journals Industrial robot trajectory planning based on improved pso algorithm

2021 ◽  
Vol 1820 (1) ◽  
pp. 012185
Author(s):  
Shunjie Han ◽  
Xinchao Shan ◽  
Jinxin Fu ◽  
Weijin Xu ◽  
Hongyan Mi
Keyword(s):  
Trajectory Planning ◽  
Industrial Robot ◽  
Pso Algorithm ◽  
Robot Trajectory ◽  
Improved Pso ◽  
Robot Trajectory Planning

Robot Trajectory Planning Using Rational Frenet-Serret Curves

Volume 2 ◽  
2004 ◽  
Author(s):  
Reza Ravani ◽  
Ali Meghdari
Keyword(s):  
Trajectory Planning ◽  
Computer Animation ◽  
Rational Curves ◽  
Robot Arm ◽  
Robot Trajectory ◽  
Arm Motion ◽  
Sweep Surface ◽  
And Robotics ◽  
Rotation Minimizing Frame ◽  
Robot Trajectory Planning

The aim of this paper is to demonstrate that the techniques of Computer Aided Geometric Design such as spatial rational curves and surfaces could be applied to Kinematics, Computer Animation and Robotics. For this purpose we represent a method which utilizes a special class of rational curves called Rational Frenet-Serret (RF) [8] curves for robot trajectory planning. RF curves distinguished by the property that the motion of their Frenet-Serret frame is rational. We describe an algorithm for interpolation of positions by a rational Frenet-Serret motion. Further more we provide an analysis on spatial frames (Frenet-Serret frame and Rotation Minimizing frame) for smooth robot arm motion and investigate their applications in sweep surface modeling.

Robot trajectory planning using a genetic algorithm

1996 ◽  
Author(s):  
Daniel J. Pack ◽  
Gregory J. Toussaint ◽  
Randy L. Haupt
Keyword(s):  
Genetic Algorithm ◽  
Trajectory Planning ◽  
Robot Trajectory ◽  
Robot Trajectory Planning

Recent Advances in Robot Trajectory Planning in a Dynamic Environment

2021 ◽  
Vol 14 ◽  
Author(s):  
Hongxin Zhang ◽  
Rongzijun Shu ◽  
Guangsen Li
Keyword(s):  
Trajectory Planning ◽  
Dynamic Environment ◽  
Local Planning ◽  
Robot Trajectory ◽  
Recent Advances ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle ◽  
Task Collaboration ◽  
Global Planning ◽  
Robot Trajectory Planning

Background: Trajectory planning is important to research in robotics. As the application environment changes rapidly, robot trajectory planning in a static environment can no longer meet actual needs. Therefore, a lot of research has turned to robot trajectory planning in a dynamic environment. Objective: This paper aims at providing references for researchers from related fields by reviewing recent advances in robot trajectory planning in a dynamic environment. Methods: This paper reviews the latest patents and current representative articles related to robot trajectory planning in a dynamic environment and introduces some key methods of references from the aspects of algorithm, innovation and principle. Results: In this paper, we classified the researches related to robot trajectory planning in a dynamic environment in the last 10 years, introduced and analyzed the advantages of different algorithms in these patents and articles, and the future developments and potential problems in this field are discussed. Conclusion: Trajectory planning in a dynamic environment can help robots to accomplish tasks in a complex environment, improving robots’ intelligence, work efficiency and adaptability to the environment. Current research focuses on dynamic obstacle avoidance, parameter optimization, real-time planning, and efficient work, which can be used to solve robot trajectory planning in a dynamic environment. In terms of the combination of multiple algorithms, multi-sensor information fusion, the combination of local planning and global planning, and multi-robot and multi-task collaboration, more improvements and innovations are needed. It should create more patents on robot trajectory planning in a dynamic environment.

Paint thickness simulation for painting robot trajectory planning: a review

2017 ◽  
Vol 44 (5) ◽  
pp. 629-638 ◽  
Author(s):  
Yan Chen ◽  
Wenzhuo Chen ◽  
Bo Li ◽  
Gang Zhang ◽  
Weiming Zhang
Keyword(s):  
Trajectory Planning ◽  
Complex Surface ◽  
Cfd Modeling ◽  
Content Type ◽  
Robot Trajectory ◽  
Model Study ◽  
Painting Robot ◽  
Paint Thickness ◽  
Deposition Simulation ◽  
Robot Trajectory Planning

Purpose The purposes of this paper are to review the progress of and conclude the trend for paint thickness simulation for painting robot trajectory planning. Design/methodology/approach This paper compares the explicit function-based method and computational fluid dynamics (CFD)-based method used for paint thickness simulation. Previous research is considered, and conclusions with the outlook are drawn. Findings The CFD-based paint deposition simulation is the trend for paint thickness simulation for painting robot trajectory planning. However, the calculation of paint thickness resulting from dynamically painting complex surface remains to be researched, which needs to build an appropriate CFD model, study approaches to dynamic painting simulation and investigate the simulation with continuously changing painting parameters. Originality/value This paper illustrates that the CFD-based method is the trend for the paint thickness simulation for painting robot trajectory planning. Current studies have been analyzed, and techniques of CFD modeling have also been summarized, which is vital for future study.

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