In order for humans and robots to interact in an effective and instinctive manner, robots must obtain information about the human emotional state in response to the robot's actions. This is important as the presence of robot in human living environment has become tremendously increasing. Consequently, we believed that it is necessary to investigate how human feel about this situation and if robot can understand those human emotions, collaboration with human can be much better. In order to investigate the human emotions, we applied a kansei survey method based on a kansei engineering technology. We request a number of participants to take part in our experiment where they will be in the same environment of where a robot is working on some tasks. The participants will answer those questions in the survey based on what they feel about working together with moving robot. The overall goal is, in fact, to predict in the least possible time which area in the vicinity of the robot the human is heading to. This paper describes the results of our findings about how human feel when collaborating with robot(s).
Product disassembly is a vital strategy for industrial recycling and remanufacturing which generates the desired parts and/or subassemblies by means of separation of a product into its elements. In order to increase disassembly capacity while maintaining the parts quality, new standards had to be established. Manual disassembly work perform by human will create inconsistency in the quality, efficiency, as well as time consuming, whereby it is believe that those weaknesses can be overcome by an automated performance. Therefore, this research work will re-evaluate the existing approach of disassembly process; reverse-assembly method in disassemble a mini toy car. The design methodology is conducted to verify the disassembly process performance and identify factors affecting the performance. The disassembly process experiment will be conducted in two ways; manual and semi-automated disassembly. This paper reviews the design process of the proposed experimental methodology. The important components of the experimental methodology are discussed in this paper.
In order for humans and robots to interact in an effective and instinctive manner, robots must obtain information about the human emotional state in response to the robots actions. This is important as the presence of robot in manufacturing industry is very wide and robot plays a big role in the emerging of automation manufacturing technology. Consequently, we believed that it is necessary to investigate how human feel about this situation and if robot can understand those human emotions, collaboration with human can be much better. In order to investigate the human emotions, we applied akanseisurvey method based on akanseiengineering technology. We request a number of participants to take part in our experiment where they will be in the same environment of where a robot is working on some tasks. The participants will answer those questions in the survey based on what they feel about working together with moving robot. The overall goal is, in fact, to predict in which area in the vicinity of the robot that the human is heading to, especially in term of humans feeling, so that by understanding how human feels of working together with robots, perhaps we can create a better working environment. This paper describes the results of our findings about how human feel when collaborating with robot (s).
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