• Journal of Communications and Networks
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• 제17권5호
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• pp.506-516
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• 2015

Wireless sensor networks (WSNs) are generally comprised of densely deployed sensor nodes, which results in highly redundant sensor data transmissions and energy waste. Since the sensor nodes depend on batteries for energy, previous studies have focused on designing energy-efficient medium access control (MAC) protocols to extend the network lifetime. However, the energy-efficient protocols induce an extra end-to-end delay, and therefore recent increase in focus on WSNs has led to timely and reliable communication protocols for mission-critical applications. In this paper, we propose an energy efficient and delay guaranteeing node scheduling scheme inspired by biological systems, which have gained considerable attention as a computing and problem solving technique.With the identification of analogies between cellular signaling systems and WSN systems, we formulate a new mathematical model that considers the networking challenges of WSNs. The proposed bio-inspired algorithm determines the state of the sensor node, as required by each application and as determined by the local environmental conditions and the states of the adjacent nodes. A control analysis shows that the proposed bio-inspired scheme guarantees the system stability by controlling the parameters of each node. Simulation results also indicate that the proposed scheme provides significant energy savings, as well as reliable delay guarantees by controlling the states of the sensor nodes.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2011년도 춘계학술대회 논문집
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• pp.297-298
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• 2011

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1020-1024
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• 2005

In this paper, an approach to dynamic systems control is addressed based on exploiting the potential features of the new nonlinear neural oscillator. Neural oscillators have recently enabled robots to exhibit natural dynamics using their robustness and entrainment properties. To technically accomplish this objective, the neural oscillator should be connected to the robot joints under the sensory feedback. This also requires the neural oscillator to adapt to the non-periodic nature of arbitrary input patterns. However, even in the most widely-used Matsuoka oscillator, when an unknown quasi-periodic or non-periodic signal is applied, its output signal is not always closely entrained. Therefore, current neural oscillators may not be applied to the precise control of the dynamic systems response. We illustrate the enhanced entrainment properties of the new neural oscillator by numerical simulation and show the possibility for implementation to control a variety of dynamic systems. It is verified that the oscillator can produce rhythmic signals for generating actuator signals which can be naturally modified by incorporating sensory feedback to adapt to outer circumstances.

• 제어로봇시스템학회논문지
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• 제12권4호
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• pp.307-314
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• 2006

In this paper, we present a comprehensive study for the development of quadruped walking robot. To understand the walking posture of a tetrapod animal, we begin with a careful observation on the skeletal system of tertapod animals. From taking a side view of their skeletal system, it is noted that their fore limbs and hind limbs perform characteristic roles during walking. Moreover, the widths of footprints and energy efficiency in walking have a close relationship through taking a front view of their walking posture. According to these observations, we present a control method where the kinematical solutions are not necessary because we develop a new rhythmic gait pattern for the quadruped walking robot. Though the proposed control method and rhythmic pattern are simple, they can provide the suitable motion planning for the robot since the resultant movement is based on the animal's movements. The validity of the proposed idea is demonstrated through dynamic simulations.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.624-636
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• 2006

This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.

• International Journal of Control, Automation, and Systems
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• 제4권2호
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• pp.227-235
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• 2006

For a sophisticated humanoid that explores and learns its environment and interacts with humans, anthropomorphic physical behavior is much desired. The human vision system orients each eye with three-degree-of-freedom (3-DOF) in the directions of horizontal, vertical and torsional axes. Thus, in order to accurately replicate human vision system, it is imperative to have a simulator with 3-DOF end-effector. We present a 3-DOF anthropomorphic oculomotor system that reproduces realistic human eye movements for human-sized humanoid applications. The parallel link architecture of the oculomotor system is sized and designed to match the performance capabilities of the human vision. In this paper, a biologically-inspired mechanical design and the structural kinematics of the prototype are described in detail. The motility of the prototype in each axis of rotation was replicated through computer simulation, while performance tests comparable to human eye movements were recorded.

• 제어로봇시스템학회논문지
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• 제16권11호
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• pp.1082-1088
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• 2010

In this paper, we propose a new gel-type biomimetic variable-focus lens system. The miniaturization of conventional lens system is limited due to the use of a set of glass lenses for adjusting the focal length. Biologically inspired by the focus adjustment mechanism of the human eye, a gel-type single lens system with variable-focus is presented. The proposed system consists of a gel-type lens, mechanical parts such as body, rotation ring, and winding-type SMA actuator. In addition, the proposed system is designed to operate with a simple and miniaturized mechanical structure using a new attachment and driving mechanism. The focusing performance of the proposed system is verified through a series of experiments and measurements of the shape of the lens using tomography.

• Advances in robotics research
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• 제1권1호
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• pp.101-126
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• 2014

In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions are achieved by a phase switching network (PSN) module. The combination of these modules generates various locomotion patterns and a reactive obstacle avoidance behavior. The behavior is driven by sensor inputs, to which additional neural preprocessing networks are applied. The complete neural circuitry is developed and tested using a physics simulation environment. This study verifies that the neural modules can serve a general purpose regardless of the robot's specific embodiment. We also believe that our neural modules can be important components for locomotion generation in other complex robotic systems or they can serve as useful modules for other module-based neural control applications.

• Journal of Electrical Engineering and Technology
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• 제10권6호
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• pp.2420-2426
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• 2015

This paper proposes an evolutionary optimization approach for optimal hopping of humanoid robots. In the proposed approach, the hopping trajectory is generated by a central pattern generator (CPG). The CPG is one of the biologically inspired approaches, and it generates rhythmic signals by using neural oscillators. During the hopping motion, the disturbance caused by the ground reaction forces is compensated for by utilizing the sensory feedback in the CPG. Posture control is essential for a stable hopping motion. A posture controller is utilized to maintain the balance of the humanoid robot while hopping. In addition, a compliance controller using a virtual spring-damper model is applied for stable landing. For optimal hopping, the optimization of the hopping motion is formulated as a minimization problem with equality constraints. To solve this problem, two-phase evolutionary programming is employed. The proposed approach is verified through computer simulations using a simulated model of the small-sized humanoid robot platform DARwIn-OP.

• 인터넷정보학회논문지
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• 제17권5호
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• pp.17-23
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• 2016

무선 센서 엑츄에이터 네트워크(WSAN) 시스템은 기존의 무선 센서 네트워크(WSN)에서 엑츄에이터 기능을 추가한 센서 노드들을 연결하여 망을 구성하는 시스템이다. 엑츄에이터는 센서 노드와 함께 작동하며, 재난구호, 군용 감시체계, 건강 모니터링 및 기반시설 보안 등의 여러 응용분야에 적용된다. 이러한 응용분야는 적시에 정확하게 작동하여 데이터를 신뢰성 있게 전달하는 능력이 요구된다. 생물학적으로 영감을 받은 모델링 기법은 개별적인 단순함을 유지하면서 동시에 강인성과 확장성, 적응성을 달성할 수 있는 기법으로 최근 상당한 관심을 받아오고 있다. 본 논문에서는 생물학적 메커니즘 중 전염병 전파 모델을 기반으로 이산 동적 모델을 제안하고 WSAN 시스템에 적용하고자 한다. 이를 위해 에너지 소모를 최소화하면서 동시에 시간지연 구속조건을 갖는 데이터 전파를 위한 노드 스케줄링 기법을 제안한다. 제안된 기법의 평형 상태 분석과 제어이론을 바탕으로 시스템의 안정성을 분석한 후 시뮬레이션 결과를 통해 요구 지연 시간을 만족하는 동시에 에너지 소모를 줄이는 성능을 검증한다.