• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.761-762
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• 2012

• Advances in robotics research
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• v.2 no.1
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• pp.1-11
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• 2018

To monitor the environment and determine the source of a pollutant gradient using a multiple robot swarm, we propose a hybrid algorithm that combines two bio-inspired algorithms mimicking chemotaxis and pheromones of bacteria. The algorithm is implemented in virtual robot agents in a simulator to evaluate their feasibility and efficiency in gradient maps with different sizes. Simulation results show that the chemotaxis controller guided robot agents to the locations with higher pollutant concentrations, while the pheromone marked in a virtual field increased the efficiency of the search by reducing the visiting redundancy. The number of steps required to reach the target point did not increase proportionally as the map size increased, but were less than those in the linear whole-map search method. Furthermore, the robot agents could function with simple sensor composition, minimum information about the map, and low calculation capacity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.1107-1108
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• 2013

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.325-326
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• 2010

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.264-269
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• 2019

This paper presents mechanical design and control of a bio-inspired legged robot. To achieve a fast legged running mechanism, a novel linkage leg structure is designed based on hind legs of domestic cats. The skeletomuscular system and parallel leg movement of a cat are analyzed and applied to determine the link parameters. The hierarchical control architecture is designed according to the biological data to generate and modulate desired gaits. The effectiveness of the leg mechanism design and control is verified experimentally. The legged robot runs at a speed of 46 km/h, which is comparatively higher speed than other existing legged robots.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.57-66
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• 2014

This paper describes the design concept of a bio-inspired legged underwater and estimating its performance by implementing simulations. Especially the leg structure of an underwater organism, diving beetles, is fully adopted to our designing to employ its efficiency for swimming. To make it possible for the robot to both walk and swim, the transformable kinematic model according to applications of the leg is proposed. To aid in the robot development and estimate swimming performance of the robot in advance, an underwater simulator has been constructed and an approximated model based on the developing robot was set up in the simulation. Furthermore, previous work that we have done, the swimming locomotion produced by a swimming patten generator based on the control parameters, is briefly mentioned in the paper and adopted to the simulation for extensive studies such as path planning and control techniques. Through the results, we established the strategy of leg joints which make the robot swim in the three dimensional space to reach effective controls.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.53-54
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• 2013

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.782-790
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• 2013

In this paper, we propose a better solution for swimming plans of an articulated underwater robot, Crabster, with a view point of biomimetics. As a biomimetic model of underwater organisms, we chose diving beetles structurally similar to Crabster. Various swimming locomotion of the diving beetle has been observed and sorted by robotics technology through experiments with a high-speed camera and image processing software Image J. Subsequently, coordinated patterns of rhythmic movements of the diving beetle are reproduced by simple control parameters in a parameter space which make it easy to control trajectories and velocities of legs. Furthermore, a simulation was implemented with an approximated model to predict the motion of the robot under development based on the classified forward and turning locomotion. Consequently, we confirmed the applicability of parameterized leg locomotion to the articulated underwater robot through the simulated results by the approximated model.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.193-200
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• 2012

Mobility is one of the most important issues for search and rescue robots. To increase mobility for small size robot we have focused on the mechanism and algorithm inspired from centipede. In spite of small size, using many legs and flexible long body, centipede can overcome high obstacles and move in rough terrains stably. This research focused on those points and imitated their legs and body that are good for obstacle negotiation. Based on similarity of a centipede's legs and tracks, serially connected tracks are used for climbing obstacles higher than the robot's height. And a centipede perceives environments using antennae on its head instead of eyes. Inspired from that, 3 IR sensors are attached on the front, top and bottom of the first module to imitate the antenna. Using the information gotten from the sensors, the robot decides next behavior automatically. In experiments, the robot can climb up to 45 cm height vertical wall and it is 600 % of the robot's height and 58 % of the robot's length.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.456-462
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• 2014

In this paper, we present a deployable bio-inspired robot called the Pillbot-light, which utilizes a safe autonomous navigation system. The Pillbot-light is mounted the station robot, and can be operated in a disaster relief operation or military operation. However, the Pilbot-light has a challenge to navigate autonomously because the Pilbot-light cannot be equipped with various sensors. As a result, we propose a new robot system for autonomous navigation that the station robot controls Pillbot-light equipped with vision camera and CPU of high performance. This system detects obstacles based on the edge extraction using vision camera. Also, it cannot only achieve path planning using the hazard cost function, but also localization using the Particle Filter. And this system is verified by simulation and experiment.