资源论文Generating Tests for Robotized Painting Using Constraint Programming

Generating Tests for Robotized Painting Using Constraint Programming

2019-11-25 | |  53 |   44 |   0
Abstract Designing industrial robot systems for welding, painting, and assembly, is challenging because they must perform with high precision, speed, and endurance. ABB Robotics has specialized in building highly reliable and safe robotized paint systems using an integrated process control system. However, current validation practices are mainly limited to manual test scenarios, which makes it difficult to exercise important aspects of a paint robot system, such as the need to coordinate the timing of paint activation with the robot motion control. To address these challenges, we have developed and deployed a cost-effective, automated test generation technique aimed at validating the timing behavior of the process control system. The approach is based on a constraint optimization model written in Prolog. This model has been integrated into an automated continuous integration environment, allowing the model to be solved on demand prior to test execution, which allows us to obtain the most optimal and diverse set of test scenarios for the current system configuration.

上一篇:Proximal Gradient Temporal Difference Learning Algorithms

下一篇:A Decision Procedure for (Co)datatypes in SMT Solvers

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...