A quantitative investigation of accuracy and repeatability for deployment of mobile collaborative robots in high-value manufacturing
Amine Hifi, William E. Jackson, Charalampos Loukas, Alastair Poole, Ehsan Mohseni, Gareth Pierce, Charles MacLeod, Gordon Dobie, T. O’Hare, Geoffrey D. Munro, J. O'Brian-O'Reilly, R. W. K. Vithanage
- 发表年份
- 2025
- 引用次数
- 2
摘要
Abstract Current inspection stations often employ fixed arm robots that allow for accurate repetitive inspection but lack flexibility in adapting to new components or orientations and are used for conventionally fixtured parts in a linear manufacturing approach. Recent advances in mobile robotic platforms with updated sensor technologies have improved localization and path planning capabilities, making them a candidate for bringing inspection processes directly to parts at different points in the manufacturing cycle, potentially helping to maintain schedule. However, mobile platforms introduce additional challenges in positional uncertainty which is higher than fixed systems due to the lack of a fixed calibrated location, posing challenges for position-sensitive inspection applications. The focus of this study is to assess the positional accuracy and repeatability of such mobile manipulator platforms and a KUKA KMR iiwa was selected for this study due to its integration of robot arm and mobile base within a single product. The accuracy and repeatability of the mobile platform were evaluated through a series of tests using a precision laser tracker to evaluate the performance of its integrated feature mapping, the effect of various speeds on positional accuracy, and the efficiency of the omnidirectional wheels for a range of translation orientations. Experimental evaluation revealed that enabling feature mapping substantially improved the KUKA KMR iiwa’s performance, with accuracy gains and error reductions exceeding 90%. Repeatability errors were measured to be under 7 mm with mapping activated and around 2.5 mm in practical scenarios, demonstrating that mobile manipulators, incorporating both the manipulator and platform, are a step towards flexible manufacturing inspection scenarios and provide a diverse alternative to traditional fixed-base industrial manipulators.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991