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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 require light weight, high torque and high speed actuators to be able to walk and run. For conventional gears with a fixed gear ratio the product of torque and velocity is constant. On the other hand desired motions require maximum torque and speed. In this paper it is shown that with a variable gear ratio it is possible to vary the relation between torque and velocity. This is achieved by introducing systems of rods and levers to move the joints of our humanoid robot ”Sweaty II”. On the basis of a variable gear ratio low speed and high torque can be achieved for those joint angles, which require this motion mode, whereas high speed and low torque can be realized for those joint angles, where it is favorable for the desired motion.
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.
This paper discusses a technological solution to real-time road transportation optimization using a commercial multi-agent based system, LS/ATN, which has been proven through real-world deployment to reduce transportation costs for both small and large fleets in the full and part load business. Subsequent to describing the real-time optimization approach, we discuss how the platform is currently evolving to accept live data from vehicles in the fleet in order to improve optimization accuracy. A selection of the predominant pervasive technologies available today for enhancing intelligent route optimization is described.
In this paper we propose a motion framework forbipedal robots that decouples motion definitions from stabilizingthe robot. This simplifies motion definitions yet allows dynamicmotion adaptations. Two applications, walking and stopping onone leg, demonstrate the power of the framework. We show thatour framework is able to perform walking and stopping on one legeven under extreme conditions and improves walking benchmarkssignificantly in the RoboCup 3D soccer simulation domain.
Learning to Walk With Toes
(2020)
This paper explains how a model-free (with respect to the robot model and the behavior to learn) approach can facilitate learning to walk from scratch. It is applied to a simulated Nao robot with toes. Results show an improvement of 30% in speed compared to a model without toes and also compared to our model-based approach, but with less stability.
In previous work we [1] and other authors (e.g. [2]) have shown that agent-based systems are successful in optimizing delivery plans of single logistics companies and are meanwhile successfully productive in industry. In this paper we show that agent-based systems are particularly useful to also optimize transport across logistics companies. In intercompany optimization, privacy is of major importance between the otherwise competing companies. Some data has to be treated strictly private like the cost model or the constraint model. Other data like order information has to be shared. However, typically the amount of orders released to other companies has also to be limited. We show that our agent-based approach can be easily fine tuned to trade off privacy against the benefit of cooperation.
This paper describes the magmaOffenburg 3D simulation team trying to qualify for RoboCup 2011. While last year’s TDP focused on the tool set created for 3D simulation in this year we describe the further improvement in this tools as well as some new features we implemented focusing on heterogeneous robot models which seem to be used in RoboCup 2012.
An additional tool was written to simply generate situation-dependent strategies. Furthermore some tools, described last year, are now integrated in one single GUI to easy things up.