Spatially Situated EndUser Robot Programming in Augmented Reality Nowadays, industrial robots are being programmed using proprietary tools developed by robot manufacturer. A skilled robot programmer is needed to create even as simple task as pick a wellknown object and put it somewhere else. Contrary, in everyday life people are using enduser programming to make different electronic devices work in expected manner, without even noticing they are actually programming. We propose augmented realityenabled enduser programming system allowing regular shopfloor workers to program industrial robotic tasks. The user interface prototype for this system was evaluated in the user study with 7 participants with respect to usability, mental workload and user experience.

Combining Interactive Spatial Augmented Reality with HeadMounted Display for EndUser Collaborative Robot Programming This paper proposes an intuitive approach for collaborative robot enduser programming using a combination of interactive spatial augmented reality (ISAR) and headmounted display (HMD). It aims to reduce userxe2x80x99s workload and to let the user program the robot faster than in classical approaches (e.g. kinesthetic teaching). The proposed approach, where user is using a mixedreality HMD xe2x80x93 Microsoft HoloLens xe2x80x93 and touchenabled table with SAR projected interface as input devices, is compared to a baseline approach, where robotxe2x80x99s arms and a touchenabled table are used as input devices. Main advantages of the proposed approach are the possibility to program the collaborative workspace without the presence of the robot, its speed in comparison to the kinesthetic teaching and an ability to quickly visualize learned program instructions, in form of virtual objects, to enhance the usersxe2x80x99 orientation within those programs. The approach was evaluated on a set of 20 users using the withinsubject experiment design. Evaluation consisted of two pick and place tasks, where users had to start from the scratch as well as to update the existing program. Based on the experiment results, the proposed approach is better in qualitative measures by 33.84% and by 28.46% in quantitative measures over the baseline approach for both tasks.