Clustering Method for Monte Carlo Model Predictive Control. Issue 14 (2021)

• Record Type: Journal Article
• Authors: Toda, Tatsuya; Nakatani, Shintaro; Date, Hisashi
• Is Part Of: IFAC-PapersOnLine. Volume 54:Issue 14(2021)
• Page Start: 251
• Page End: 256
• Publication Date: 2021
• Subjects: Model Predictive Control -- Multimodality -- Monte Carlo method -- Clustering; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.10.361
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Monte Carlo Model Predictive Control is a variant of a sampling-based model predictive control, which is suitable for extensively parallel processors. In this study, we focus on the multimodality of the objective function and propose a clustering method to cope with it. As an application of multimodality, we consider a navigation problem of a mobile robot that avoids some obstacles. Simulation results show that our method is effective when the avoiding path splits into pieces.