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Opportunities and Challenges in Mixed-Reality for an Inclusive Human-Robot Collaboration Environment
(2018)
This paper presents an approach to enhance robot control using Mixed-Reality. It highlights the opportunities and challenges in the interaction design to achieve a Human-Robot Collaborative environment. In fact, Human-Robot Collaboration is the perfect space for social inclusion. It enables people, who suffer severe physical impairments, to interact with the environment by providing them movement control of an external robotic arm. Now, when discussing about robot control it is important to reduce the visual-split that different input and output modalities carry. Therefore, Mixed-Reality is of particular interest when trying to ease communication between humans and robotic systems.
A Robust Interface for Head Motion based Control of a Robot Arm using MARG and Visual Sensors
(2018)
Head-controlled human machine interfaces have gained popularity over the past years, especially in the restoration of the autonomy of severely disabled people, like tetraplegics. These interfaces need to be reliable and robust regarding the environmental conditions to guarantee safety of the user and enable a direct interaction between a human and a machine. This paper presents a hybrid MARG and visual sensor system for head orientation estimation which is in this case used to teleoperate a robotic arm. The system contains a Magnetic Angular Rate Gravity (MARG)-sensor and a Tobii eye tracker 4C. A MARG sensor consists of tri-axis accelerometer, gyroscope as well as a magnetometer which enable a complete measurement of orientation relative to the direction of gravity and magnetic field of the earth. The tri-axis magnetometer is sensitive to external magnetic fields which result in incorrect orientation estimation from the sensor fusion process. In this work the Tobii eye tracker 4C is used to increase head orientation estimation because it also features head tracking even though it is commonly used for eye tracking. This type of visual sensor does not suffer magnetic drift. However, it computes orientation data only, if a user is detectable. Within this work a state machine is presented which enables data fusion of the MARG and visual sensor to improve orientation estimation. The fusion of the orientation data of MARG and visual sensors enables a robust interface, which is immune against external magnetic fields. Therefore, it increases the safety of the human machine interaction.
In this experimental work we present a novel electrolyzer system for the production of hydrogen and oxygen at high pressure levels without an additional mechanical compressor. Due to its control strategies, the operation conditions for this electrolyzer can be kept optimal for each load situation of the system. Furthermore, the novel system design allows for dynamic long-term operation as well as for easy maintainability. Therefore, the device meets the requirements for prospective power-to-gas applications, especially, in order to store excess energy from renewable sources. A laboratory scale device has been developed and high-pressure operation was validated. We also studied the long-term stability of the system by applying dynamic load cycles with load changes every 30 sec. After 80 h of operation the used membrane electrode assembly (MEA) was investigated by means of SEM, EDX and XRD analysis.