Variation Analysis Toolbox for Non-Nominal Path Planning for Industrial Robots

2007 ◽  
Author(s):  
Lars Lindkvist ◽  
Rikard So¨derberg ◽  
Johan S. Carlson
Keyword(s):  
Path Planning ◽  
Process Design ◽  
Manufacturing Process ◽  
Industrial Robots ◽  
Test Cases ◽  
Variation Analysis ◽  
On Line ◽  
Geometrical Variation ◽  
Assembly Analysis ◽  
Robot Path

Industrial robots are frequently used in the manufacturing process. One important aspect in the manufacturing process design is to assure that there exists a collision-free assembly path for each part and subassembly including the assembly equipment, e.g. a robot. In order to reduce the need of physical verification the automotive industry uses digital mock-up tools with collision checking for this kind of geometrical assembly analysis. However, in real production, all equipment, parts and subassemblies are affected by geometrical variation, often resulting in conflicts and on-line adjustments of off-line generated assembly paths. This paper presents a variation analysis toolbox for path planning for industrial robots. This toolbox can help to avoid problems with on-line adjustments. The variation analysis includes the variation in joints and actuators in the robot and can also be used by robot manufacturers when designing new robots. A new tool for variation analysis of a robot path is presented. Also, variation analysis of the product at the assembly line is used to enhance the off-line generated assembly paths. With better knowledge of the variation in the robot and product we can allow the assembly path to reach closer to areas of low variation, while avoiding areas of high variation. The proposed approach is illustrated with test cases.

Path Planning in a Mobile Robot

2019 ◽  
pp. 582-608
Author(s):  
Diego Alexander Tibaduiza Burgos ◽  
Maribel Anaya Vejar
Keyword(s):  
Genetic Algorithms ◽  
Path Planning ◽  
Mobile Robot ◽  
Fitness Function ◽  
Experimental Setup ◽  
Robot Path Planning ◽  
Natural Evolution ◽  
On Line ◽  
Planning Problems ◽  
Robot Path

This chapter presents the development and implementation of three approaches that contribute to solving the mobile robot path planning problems in dynamic and static environments. The algorithms include some items regarding the implementation of on-line and off-line situations in an environment with static and mobile obstacles. A first technique involves the use of genetic algorithms where a fitness function and the emulation of the natural evolution are used to find a free-collision path. The second and third techniques consider the use of potential fields for path planning using two different ways. Brief descriptions of the techniques and experimental setup used to test the algorithms are also included. Finally, the results applying the algorithms using different obstacle configurations are presented and discussed.

Path Planning in a Mobile Robot

2013 ◽  
pp. 123-147
Author(s):  
Diego Alexander Tibaduiza Burgos ◽  
Maribel Anaya Vejar
Keyword(s):  
Genetic Algorithms ◽  
Path Planning ◽  
Mobile Robot ◽  
Fitness Function ◽  
Experimental Setup ◽  
Robot Path Planning ◽  
Natural Evolution ◽  
On Line ◽  
Planning Problems ◽  
Robot Path

This chapter presents the development and implementation of three approaches that contribute to solving the mobile robot path planning problems in dynamic and static environments. The algorithms include some items regarding the implementation of on-line and off-line situations in an environment with static and mobile obstacles. A first technique involves the use of genetic algorithms where a fitness function and the emulation of the natural evolution are used to find a free-collision path. The second and third techniques consider the use of potential fields for path planning using two different ways. Brief descriptions of the techniques and experimental setup used to test the algorithms are also included. Finally, the results applying the algorithms using different obstacle configurations are presented and discussed.

Numerical Potential Field Techniques for Robot Path Planning.

1989 ◽  
Author(s):  
Jerome Barraquand ◽  
Bruno Langlois ◽  
Jean-Claude Latombe
Keyword(s):  
Path Planning ◽  
Potential Field ◽  
Robot Path Planning ◽  
Field Techniques ◽  
Robot Path

scholarly journals Resource and dependency based test case generation for RESTful Web services

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Man Zhang ◽  
Bogdan Marculescu ◽  
Andrea Arcuri
Keyword(s):  
Web Services ◽  
Domain Knowledge ◽  
Automated System ◽  
Test Case ◽  
Test Cases ◽  
Evolutionary Search ◽  
Sampling Strategies ◽  
Mutation Operators ◽  
On Line ◽  
Restful Web Services

AbstractNowadays, RESTful web services are widely used for building enterprise applications. REST is not a protocol, but rather it defines a set of guidelines on how to design APIs to access and manipulate resources using HTTP over a network. In this paper, we propose an enhanced search-based method for automated system test generation for RESTful web services, by exploiting domain knowledge on the handling of HTTP resources. The proposed techniques use domain knowledge specific to RESTful web services and a set of effective templates to structure test actions (i.e., ordered sequences of HTTP calls) within an individual in the evolutionary search. The action templates are developed based on the semantics of HTTP methods and are used to manipulate the web services’ resources. In addition, we propose five novel sampling strategies with four sampling methods (i.e., resource-based sampling) for the test cases that can use one or more of these templates. The strategies are further supported with a set of new, specialized mutation operators (i.e., resource-based mutation) in the evolutionary search that take into account the use of these resources in the generated test cases. Moreover, we propose a novel dependency handling to detect possible dependencies among the resources in the tested applications. The resource-based sampling and mutations are then enhanced by exploiting the information of these detected dependencies. To evaluate our approach, we implemented it as an extension to the EvoMaster tool, and conducted an empirical study with two selected baselines on 7 open-source and 12 synthetic RESTful web services. Results show that our novel resource-based approach with dependency handling obtains a significant improvement in performance over the baselines, e.g., up to + 130.7% relative improvement (growing from + 27.9% to + 64.3%) on line coverage.

Sign in / Sign up

Export Citation Format

Share Document