Development of Industrial Robot System with 5th Generation Mobile Communication System

We experimented the configuration of a 5th generation mobile communication system (5G) for factory automation (FA) systems consisting of industrial robots and three-dimensional measurement sensors. We examined the configuration of system components, on the basis of which we developed an experimental FA system. In addition, we confirmed that the need for communication lines is eliminated as 5G greatly reduces the production preparation time when rearranging the parts of the developed FA system.19th International Conference on Control, Automation and Systems (ICCAS 2019), October 15-18, 2019, Jeju, Kore

Preliminary Test of Affective Virtual Reality Scenes with Head Mount Display for Emotion Elicitation Experiment

Emotion elicitation experiments are conducted to collect biological signals from a subject who is in a state　of emotion. The recorded signals are used as training/test dataset for constructing an emotion recognition system by　means of machine learning. In conventional emotion elicitation experiments, affective images or videos were provided　for a subject to draw out an emotion from them. However, the authors have concerns about the effectiveness. To surely　evoke a specific emotion from subjects, we have produced several Virtual Reality (VR) scenes and provided the　subjects with the scenes through a Head Mount Display (HMD) in emotion elicitation experiments. Usability and　effectiveness of the VR scenes with the HMD for emotion elicitation were experimentally verified. It was confirmed　that experience of the VR scenes with the HMD was effective in evoking emotions, but we have to improve how　subjects learn a way of playing VR scenes and provide measures against VR sickness at any cost. Moreover, Support　Vector Machine classifiers as an emotion recognition system were constructed using the biological signals measured　from the subjects in the emotion elicitation experiments.2017 17th International Conference on Control, Automation and Systems (ICCAS 2017), Oct. 18-21, 2017, Ramada Plaza, Jeju, Kore

Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments