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|Title:||Methodologies for immersive robot programming in an augmented reality environment|
|Authors:||Ong, S.K. |
Curve learning Bayesian neural networks
|Source:||Ong, S.K.,Chong, J.W.S.,Nee, A.Y.C. (2006). Methodologies for immersive robot programming in an augmented reality environment. Proceedings - GRAPHITE 2006: 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia : 237-244. ScholarBank@NUS Repository. https://doi.org/10.1145/1174429.1174470|
|Abstract:||Advancements in robotics have gained much momentum in recent years. Industrial robotic systems are increasingly being used outside the factory floor, evident by the growing presence of service robots in personal environments. In light of these trends, there is currently a pressing need of identifying new ways of programming robots safely, quickly and more intuitively. These methods should focus on service robots and address long outstanding Human-Robot Interaction issues in industrial robotics simultaneously. In this paper, the potential of using an Augmented Reality (AR) environment to facilitate immersive robot programming in unknown environments is explored. The benefits of an AR environment over conventional robot programming approaches are discussed, followed by a description of the Robot Programming using AR (RPAR) system developed in this research. New methodologies for programming two classes of robotic tasks using RPAR are proposed. A number of case studies are presented and the results discussed.|
|Source Title:||Proceedings - GRAPHITE 2006: 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia|
|Appears in Collections:||Staff Publications|
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