Reference : Collaborative Nonlinear Model-Predictive Motion Planning and Control of Mobile Transp...
Scientific journals : Article
Engineering, computing & technology : Computer science
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/17299
Collaborative Nonlinear Model-Predictive Motion Planning and Control of Mobile Transport Robots for a Highly Flexible Production System
English
Wangmanaopituk, Suparchoek [Sirindhorn International Institute of Technology, Thammasat University, Thailand > School of Information, Computer and Communication Technology]
Voos, Holger mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit > ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)]
Kongprawechnon, Waree [Sirindhorn International Institute of Technology, Thammasat University, Thailand > School of Information, Computer and Communication Technology]
12-Oct-2010
ScienceAsia
Science Society of Thailand
36
4
333-341
Yes (verified by ORBilu)
International
1513-1874
Bangkok
Thailand
[en] Mobile Robotics ; Flexible manufacturing ; model predictive control
[en] This study is based on a new approach for an advanced microproduction system or highly flexible production
systems where all necessary production and assembly processes are connected in a very flexible way using autonomous
mobile transport and handling robots. Each robot has to follow its planned paths while avoiding collisions with other robots.
In addition, problem-specific constraints for a defined microproduction system, such as limitations of the velocity and
accelerations of the robots, have to be fulfilled. This paper focuses on a two-level model predictive optimizing approach.
On a global long-term level, simple dynamic models of the robots are used to compute optimal paths under differential
constraints where a safety distance between all robots is achieved. Since many uncertainties and unforeseen events could
occur, all robots also use a nonlinear model predictive control approach on a local real-time level. This control approach
solves the path following and the collision avoidance problems in parallel, while also taking into account differential
constraints of the single robots.
http://hdl.handle.net/10993/17299

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