Knowledge growing is one of intelligence characteristics possessed by human brain. In this paper we review some fundamental theories that are appropriate for emulating this kind of intelligence in order to develop an intelligent system in Artificial Intelligence (AI) field, called brain-inspired Knowledge-Growing System (KGS). The development of this system is approached from various fields, namely psychological, mathematical, social, and electrical engineering and informatics fields. Based on the review results, we have built this system along with mechanism for growing the knowledge that consists of a model of Human Inference System (HIS), Sense-Inference-Decide and Act (SIDA) cycle, and the mathematical formulation for growing the knowledge called Observation Multi-time Arwin-Adang-Aciek-Sembiring (OMA3S) information-inferencing fusion method. In conclusion, brain-inspired KGS is a cognitive agent which is equipped with knowledge growing mechanism as its intelligent characteristic.

This paper present a particle filter for mobile robot localization also known as Monte Carlo Localization (MCL) to solve the localization problem of autonomous mobile robot. A new resampling mechanism is proposed. This new resampling mechanism enables the particle filter to converge quicker and more robust to kidnaping problem. This particle filter is simulated in MATLAB and also experimented physically using a simple autonomous mobile robot built with Lego Mindstorms NXT with 3 ultrasonic sonar and RWTH Mindstorms NXT Toolbox for MATLAB to connect the robot to MATLAB. The particle filter with the new resampling algorithm can perform very well in thesimulation as well as in physical experiments.

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This paper proposes an autopilot system that can be used to control the small scale rotorcraft during the flight test for linear-frequency-domain system identification. The input frequency swept is generated automatically as part of the autopilot control command. Therefore the bandwidth coverage and consistency of the frequency swept is guaranteed to produce high quality data for system identification. Beside that we can set the safety parameter during the flight test (maximum roll / pitch value, minimum altitude, etc) so the safety of the whole flight test is guaranteed. This autopilot for automated flight test will be tested using hardware in the loop simulator for hover flight condition. ICIUS

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