| 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  [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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