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One of the challenges in humanoid robotics is motion control. Interacting with humans requires impedance control algorithms, as well as tackling the problem of the closed kinematic chains which occur when both feet touch the ground. However, pure impedance control for totally autonomous robots is difficult to realize, as this algorithm needs very precise sensors for force and speed of the actuated parts, as well as very high sampling rates for the controller input signals. Both requirements lead to a complex and heavy weight design, which makes up for heavy machines unusable in RoboCup Soccer competitions.
A lightweight motor controller was developed that can be used for admittance and impedance control as well as for model predictive control algorithms to further improve the gait of the robot.
Biological in situ methanation: Gassing concept and feeding strategy for enhanced performance
(2017)
The expansion of fluctuating renewable electricity production from wind and solar energy requires huge storage capacities. Power-to-gas (PtG) can contribute to tackle that issue via a two-step process, the electrolytic production of hydrogen and a subsequent methanation step (with additional CO2). The resulting fully grid compatible methane, also known as synthetic natural gas (SNG), can be both stored and transported in the vast existing natural gas infrastructure.
To overcome current major drawbacks of PtG, the relatively low efficiency and the high costs, we developed an improved method for the methanation step. In our approach we use a further development of the biological in situ methanation of hydrogen in biogas plants. Because this strategy uses directly internal residual CO2 from the biogas process in the biogas plant, you neither need additional external CO2 nor special reactors. Thus, PtG is combined with the production of an upgraded highly methane rich raw biogas.
However, the low solubility of hydrogen in aqueous solutions and the exploitation of the maximum biological production rates are still an engineering challenge for high performance biological in situ methanation.
In our experiments a setup with membrane gassing turned out to be most promising to ensure a sufficient gas liquid mass transfer of the hydrogen. The monitoring of hydrogenotrophic and aceticlastic archaea showed some adaption of these microbial subgroups to the hydrogen feed.
In order to achieve high methane concentrations of more than 90 % in the raw biogas a CO2-controlled hydrogen feed flow rate is suggested. For methane concentrations lower than 90 % simple current controlled hydrogen supply can be applied.
Vorgestellt wird ein Konzept zur biologischen Methanisierung von Wasserstoff direkt in Biogasreaktoren, mit dem durch Membranbegasung der Methangehalt des Biogases auf > 96 % erhöht werden kann. Essentiell zum Erreichen solch hoher Methanwerte sind die Einhaltung eines optimalen pH-Bereichs und die Vermeidung von H2-Akkumulation. Im Falle einer Limitierung der Methanbildungsrate durch den eigentlichen anaeroben Abbauprozess der Biomasse ist auch eine externe Zufuhr von CO2 zur weiteren Methanbildung denkbar. Das Verfahren soll weiter optimiert und in einem von der Deutschen Bundesstiftung Umwelt geförderten Projekt in der Biogasanlage einer regionalen Käserei in der Praxis getestet werden. Die hier angestrebte Kombination aus dezentraler Abfallverwertung und Eigenenergieerzeugung eines lebensmittelverarbeitenden Betriebs unter Einbindung in ein intelligentes Erneuerbare Energien - Konzept soll einen zusätzlichen Mehrwert liefern.
For the RoboCup Soccer AdultSize League the humanoid robot Sweaty uses a single fully convolutional neural network to detect and localize the ball, opponents and other features on the field of play. This neural network can be trained from scratch in a few hours and is able to perform in real-time within the constraints of computational resources available on the robot. The time it takes to precess an image is approximately 11 ms. Balls and goal posts are recalled in 99 % of all cases (94.5 % for all objects) accompanied by a false detection rate of 1.2 % (5.2 % for all). The object detection and localization helped Sweaty to become finalist for the RoboCup 2017 in Nagoya.
The humanoid Sweaty was the finalist in this year’s robocup soccer championship(adult size). For the optimization of the gait and the stability, data concerning forces and torques in the ankle joints would be helpful. In the following paper the development of a six-axis force and torque sensor for the humanoid robot Sweaty is described. Since commercial sensors do not meet the demands for the sensors in Sweatys ankle joints, a new sensor was developed. As a measuring devices we used strain gauges and custom electronics based on an acam PS09. The geometry was analyzed with the FEM program ANSYS to get optimal dimensions for the measuring beams. In addition ANSYS was used to optimize the position for the strain gauges on the beam.
Autonomous humanoid robots need high torque actuators to be able to walk and run. One problem in this context is the heat generated. In this paper we propose to use water evaporation to improve cooling of the motors. Simulations based on thermodynamic calculations as well as measurements on real actuators show that, under the assumption of the load of a soccer game, cooling can be considerably improved with relatively small amounts of water.
In this paper, we propose an approach for gait phase detection for flat and inclined surfaces that can be used for an ankle-foot orthosis and the humanoid robot Sweaty. To cover different use cases, we use a rule-based algorithm. This offers the required flexibility and real-time capability. The inputs of the algorithm are inertial measurement unit and ankle joint angle signals. We show that the gait phases with the orthosis worn by a human participant and with Sweaty are reliably recognized by the algorithm under the condition of adapted transition conditions. E.g., the specificity for human gait on flat surfaces is 92 %. For the robot Sweaty, 95 % results in fully recognized gait cycles. Furthermore, the algorithm also allows the determination of the inclination angle of the ramp. The sensors of the orthosis provide 6.9 and that of the robot Sweaty 7.7 when walking onto the reference ramp with slope angle 7.9.