• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.139-140
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• 2009

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.509-515
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• 2010

In this paper, the mechanism that can walk efficiently in wet land or sand area is proposed. A vision camera is attached to the mechanism, which makes a kind of biologically inspired robot for coast guard. This visionary information enables the biologically inspired robot to react in peripheral environment by a soft-computing algorithm. In addition, the biologically inspired robot can achieve the mission appointed by a programmer connecting with outside, based on RF and Blue-tooth communication module. Therefore, the purpose of this research is the implementation of the biologically inspired robot that can operate most adaptively in sand and wet surface based on Theo Jansen mechanism.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1271-1272
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• 2010

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.159-164
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• 2011

In this study, a crab robot is implemented in H/W based on four-bar linkage mechanism and Jansen mechanism, and its kinematics is analysed. A vision camera is attached to the mechanism, which makes the proposed robot a kind of biologically inspired robot for image acquisition. Three ultrasonic sensors are adopted for obstacle avoidance. In addition, the biologically inspired robot can achieve the mission appointed by a programmer outside, based on RF and Blue-tooth communication module. For the design and implementation of a crab robot, it is need to get joint variable, a foot point, and their relation. Thus, the proposed kinematic analysis is very important process for the design and implementation of legged robots.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1477-1491
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• 2017

Inspired by the multi-scale nature of hippocampal place cells, a biologically inspired model based on a multi-scale spatial representation for goal-directed navigation is proposed in order to achieve robotic spatial cognition and autonomous navigation. First, a map of the place cells is constructed in different scales, which is used for encoding the spatial environment. Then, the firing rate of the place cells in each layer is calculated by the Gaussian function as the input of the Q-learning process. The robot decides on its next direction for movement through several candidate actions according to the rules of action selection. After several training trials, the robot can accumulate experiential knowledge and thus learn an appropriate navigation policy to find its goal. The results in simulation show that, in contrast to the other two methods(G-Q, S-Q), the multi-scale model presented in this paper is not only in line with the multi-scale nature of place cells, but also has a faster learning potential to find the optimized path to the goal. Additionally, this method also has a good ability to complete the goal-directed navigation task in large space and in the environments with obstacles.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.563-570
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• 2009

In the future, most military activities will be replaced by robots. Because of many dangerous factors in battlefield, reconnaissance should be performed by robot. Reconnaissance robot should be small for not being detected, be light and simple structure for personal portability and overcome unexpected rough terrain for mission completion. In case of small and light robot, it can't get enough friction force for movement. Therefore small reconnaissance robot need jumping function for movement. In this paper we proposed a biologically inspired jumping mechanism. And we adjusted moment and jumping angle by using four bar linkage, especially varying coupler length.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.297-298
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• 2011

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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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.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1427-1432
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• 2008

This paper describes the locomotion of a water jumping robot which attempts to emulate the fishing spider’s ability to jump on the water surface. While previous studies of the robots mimicking arthropods living on water were focused on recreating their horizontal skating motions, here we aim to achieve a vertical jumping motion. The robot jumps by pushing the water surface with rapidly released legs which were initially bent. The motion is triggered with a latch driven by the shape memory alloy actuator. The robot is capable of jumping to the maximum height of 26mm. Jumping efficiency, defined the maximum jumping height on water over the maximum jumping height on rigid ground, is 0.26 This work represents a first step toward robots that can locomote on water with superior versatility including skating and jumping.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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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.