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This paper describes the Sweaty II humanoid adult size robot trying to qualify for the RoboCup 2017 adult size humanoid competition. Sweaty came 2nd in RoboCup 2016 adult size league. The paper describes the main characteristics of Sweaty that made this success possible, and improvements that have been made or are planned to be implemented for RoboCup 2017.
In this TDP we describe a new tool created for testing the strategy layer of our soccer playing agents. It is a complete 2D simulator that simulates the games based on the decisions of 22 agents. With this tool, debugging the decision and strategy layer of our agents is much more efficient than before due to various interaction methods and complete control over the simulation.
In the future, the tool could also serve as a measure to run simulations of game series much faster than with the 3D simulator. This way, the impact of different play strategies could be evaluated much faster than before.
Technology and computer applications influence our daily lives and questions arise concerning the role of artificial intelligence and decision-making algorithms. There are warning voices, that computers can, in theory, emulate human intelligence-and exceed it. This paper points out that a replacement of humans by computers is unlikely, because human thinking is characterized by cognitive heuristics and emotions, which cannot simply be implemented in machines operating with algorithms, procedural data processing or artificial neural networks. However, we are going to share our responsibilities with superior computer systems, which are tracking and surveying all of our digital activities, whereas we have no idea of the decision-making processes inside the machines. It is shown that we need a new digital humanism defining rules of computer responsibilities to avoid digital totalism and comprehensive monitoring and controlling of individuals within the planet Earth.
The paper describes the hardware and software architecture of the developed multi MEMS sensor prototype module, consisting of ARM Cortex M4 STM32F446 microcontroller unit, five 9-axis inertial measurement units MPU9255 (3D accelerometer, 3D gyroscope, 3D magnetometer and temperature sensor) and a BMP280 barometer. The module is also equipped with WiFi wireless interface (Espressif ESP8266 chip). The module is constructed in the form of a truncated pyramid. Inertial sensors are mounted on a special basement at different angles to each other to eliminate hardware sensors drifts and to provide the capability for self-calibration. The module fuses information obtained from all types of inertial sensors (acceleration, rotation rate, magnetic field and air pressure) in order to calculate orientation and trajectory. It might be used as an Inertial Measurement Unit, Vertical Reference Unit or Attitude and Heading Reference System.
The low cost and small size of MEMS inertial sensors allows their combination into a multi sensor module in order to improve performance. However the different linear accelerations measured on different places on a rotating rigid body have to be considered for the proper fusion of the measurements. The errors in measurement of MEMS inertial sensors include deterministic imperfection, but also random noise. The gain in accuracy of using multiple sensors depends strongly on the correlation between these errors from the different sensors. Although for sensor fusion it usually assumed that the measurement errors of different sensors are uncorrelated, estimation theory shows that for the combination of the same type of sensors actually a negative correlation will be more beneficial. Therefore we describe some important and often neglected considerations for the combination of several sensors and also present some preliminary results with regard to the correlation of measurements from a simple multi sensor setup.
A novel approach of a testbed for embedded networking nodes has been conceptualized and implemented. It is based on the use of virtual nodes in a PC environment, where each node executes the original embedded code. Different nodes are running in parallel and are connected via so-called virtual interfaces. The presented approach is very efficient and allows a simple description of test cases without the need of a network simulator. Furthermore, it speeds up the process of developing new features.