• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.591-597
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• 2007

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, the new polygon based Q-learning algorithm and distributed genetic algorithms are proposed for behavior learning and evolution of collective autonomous mobile robots. And by distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning is adopted in this paper. we verify the effectiveness of the proposed method by applying it to cooperative search problem.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.105-114
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• 1999

By using the conceptual impedance and the elasticity of a serial chain of spring-damper system, a real-time collision-free trajectory generation algorithm is proposed. The reference points on a trajectory connected by the spring-damper system have a mechanism for self-Position adjustment to avoid a collision by the impedance, and the local adjustment of each reference point is propagated through the elasticity to a real robot at the end of the spring-damper system. As a result, the overall trajectory consisting of the reference points becomes free of collision with environmental obstacles and efficient having the shortest distance as possible. In this process, the reference points connected by the spring-damper system take role of virtual robot as global guidance for a real robot, and a cooperative optimization is carried out by the system of virtual robots. A control algorithm is proposed to implement the impedance for a car-like mobile robot.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.124-127
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• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.809-811
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• 2000

협조행동이 요구되는 다수의 자율이동로봇 시스템에서 각 개체는 주변환경의 인식뿐만 아니라 지속적인 환경변화에 적응할 수 있는 고도의 추론능력을 요구하고 있다. 이에 본 논문에서는 강화학습을 이용하여 동적으로 변화하는 환경에서 스스로 학습하여 대처할 수 있는 협조행동 방법을 제시하였다. 강화학습은 동물의 학습방법 연구에서 비롯되었으며, 주어진 목표를 수행하는 과정에서 개체의 행동이 목표를 성취하도록 하였을 때는 그 행동에 보상을 주어 환경의 상태에 따른 최적의 행동방법을 찾아내도록 학습하는 방법이다. 따라서 본 논문에서는 포식자들이 협조행동을 통하여 능동적으로 움직이는 먹이를 잡는 까다로운 문제에 제안한 방법을 적용하여 그 성능을 검증하였다.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.99-109
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• 2015

This study proposes a new approach to analyze the impedance and the elasticity of a serial chain of spring-damper system, areal-time collision-free trajectory generation algorithm is proposed. The reference points on a trajectory connected by the spring-damper system have a mechanism for self-position adjustment to solve a collision problem by the impedance, and the local adjustment of each reference point is propagated through the elasticity to a real robot at the end of the spring-damper system. As a result, the overall trajectory consisting of the reference points becomes free of collision with environmental obstacles and efficient having the shortest distance as possible. In this process,, the reference points connected by the spring-damper system take role of virtual robot as global guidance for a real robot, and a cooperative is carried out by the system of robots. A control technology is proposed to implement for mobile robot.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.257-264
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• 2009

This paper proposes a novel face detection method that finds tiny faces located at a long range even with low-resolution input images captured by a mobile robot. The proposed approach can locate extremely small-sized face regions of $12{\times}12$ pixels. We solve a tiny face detection problem by organizing a system that consists of multiple detectors including a mean-shift color tracker, short- and long-rage face detectors, and an omega shape detector. The proposed method adopts the long-range face detector that is well trained enough to detect tiny faces at a long range, and limiting its operation to only within a search region that is automatically determined by the mean-shift color tracker and the omega shape detector. By focusing on limiting the face search region as much as possible, the proposed method can accurately detect tiny faces at a long distance even with a low-resolution image, and decrease false positives sharply. According to the experimental results on realistic databases, the performance of the proposed approach is at a sufficiently practical level for various robot applications such as face recognition of non-cooperative users, human-following, and gesture recognition for long-range interaction.

• Journal of IKEEE
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• v.24 no.2
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• pp.638-648
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• 2020

Currently, the method of user-follwoing in intelligent cooperative robots usually based in vision system and using Lidar is common and have excellent performance. But in the closed space of Corona 19, which spread worldwide in 2020, robots for cooperation with medical staff were insignificant. This is because Medical staff are all wearing protective clothing to prevent virus infection, which is not easy to apply with existing research techniques. Therefore, in order to solve these problems in this paper, the ultrasonic sensor is separated from the transmitting and receiving parts, and based on this, this paper propose that estimating the user's position and can actively follow and cooperate with people. However, the ultrasonic sensors were partially applied by improving the Median filter in order to reduce the error caused by the short circuit in communication between hard reflection and the number of light reflections, and the operation technology was improved by applying the curvature trajectory for smooth operation in a small area. Median filter reduced the error of degree and distance by 70%, vehicle running stability was verified through the training course such as 'S' and '8' in the result.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.