• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.429-433
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• 2016

Moving robot is divided 2 kinds; one is the robot using wheels and the other has leg structure. On plat terrain, the former is better than the latter because it has fast speed and simple method to control. But on non-plat terrain, the situation is reversed. The robot using legs has slow speed but it has advantage to adjust various environments. This robot is expected to contribute to human in many fields such as rescue and exploration and so on. So walking robot is worth enough to research. In this paper, we present the design of 4-legged walking robot based on Jansen mechanism using m-Sketch and Edison Designer.

• Journal of Internet of Things and Convergence
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• v.6 no.3
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• pp.59-65
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• 2020

The Internet of Things (IoT) era, in which all items used in daily life are equipped with a network connection function, and they are closely linked to increase the convenience of life and work, has opened wide. Robots also need to develop according to the IoT environment. A use of new type of evolved fuzzy machine (EFM) for generating legged robot trajectory in IoT enviornmentms is discussed in this paper. Fuzzy system has been widely used for describing nonlinear systems. In fuzzy system, determination of antecedent and consequent structures of fuzzy model has been one of the most important problems. EFM is described which carries out evolving antecedent and consequent structure of fuzzy system for legged robot. To generate the robot trajectory, parameters of each structure in the fuzzy system are tuned automatically by the EFM. The results demonstrate the performance of the proposed approach for the legged robot.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1193-1200
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• 2015

An effective swing trajectory of legged robots is different from the swing trajectories of humans or animals because of different dynamic characteristics. Therefore, it is important to find optimal parameters through experiments. This paper proposes a real-time nonlinear programming (RTNLP) method for optimization of the swing trajectory of the legged robot. For parameterization of the trajectory, the swing trajectory is approximated to parabolic and cubic spline curves. The robotic leg is position-controlled by a high-gain controller, and a cost function is selected such that the sum of the motor inputs and tracking errors at each joint is minimized. A simplified dynamic model is used to simulate the dynamics of a robotic leg. The purpose of the simulation is to find the feasibility of the optimization problem before an actual experiment occurs. Finally, an experiment is carried out on a real robotic leg with two degrees of freedom. For both the simulation and the experiment, the design variables converge to a feasible point, reducing the cost value.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2721-2724
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• 2003

This paper deals with a manipulability analysis of multi-legged walking robots in acceleration domain, that is the dynamic manipulability analysis of walking robot. Noting that the kinematic structure of the walking robot is basically the same with that of the multiple serial robot system holding one object, the analysis method for cooperating robot is converted to that of walking robot. With the proposed method, the bound of achievable acceleration of the moving body is easily derived from the given bounds on the capabilities of Joint torques. Several walking robot examples are analyzed with proposed method under the assumption of hard contact, and presented in the paper to validate the method.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.196-202
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• 2019

Snake robots are slower than wheeled robots or legged robots, while they have an excellent terrainability in a disastrous area. Considering their advantages and disadvantages, a legged robot whose legs are snake robots, 'Quadnake' was proposed in this research. Five motions of the snake were analyzed. Applying these motions, Quadnake could implement eight kinds of motions which snake robots and quadruped walking robots can implement. As a result of it, Quadnake can have the advantages of both a snake robot and a walking robot. It is expected to move stably in a harsh terrain with snake's motion and move fast with walking.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.2
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• pp.141-148
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• 2012

This paper proposes fault tolerant gaits of a quadruped robot with feet of flat shape. Fault tolerant gaits make it possible for a legged robot to continue static walking against a leg failure. In the previous researches, it was assumed that a legged robot had feet that have point contact with the surface. When the robot is endowed with feet having flat shape, fault tolerant gaits can show better performance compared with the former gaits, especially in terms of the stride length and gait stability. In this paper, fault tolerant gaits of a quadruped robot against a locked joint failure are addressed in straight-line motion and crab walking, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.673-678
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• 2011

This paper analyzes the standing balance of four-legged robots which are useful for delivering objects or investigating of information. For this, we specify an effective model of general four-legged robots and propose a boundary condition based on the standing stability of the four-legged walking. To verify such a standing balance, we consider some exemplary free motions at the standing mode of the robot and discuss on the robot's balance margin. The analysis specified in this paper will be applicable for effective balancing control of various quadruped robotic walking.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.143-154
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• 2023

In this study, a fast motion planning method for the swing motion of a 6x6 wheel-legged robot to traverse large obstacles and gaps is proposed. The motion planning method presented in the previous paper, which was based on trajectory optimization, took up to tens of seconds and was limited to two-dimensional, structured vertical obstacles and trenches. A deep neural network based on one-dimensional Convolutional Neural Network (CNN) is introduced to generate keyframes, which are then used to represent smooth reference commands for the six leg angles along the robot's path. The network is initially trained using the behavioral cloning method with a dataset gathered from previous simulation results of the trajectory optimization. Its performance is then improved through reinforcement learning, using a one-step REINFORCE algorithm. The trained model has increased the speed of motion planning by up to 820 times and improved the success rates of obstacle crossing under harsh conditions, such as low friction and high roughness.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.329-338
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• 1994

This paper presents a novel method of path planning for a quadruped walking robot on irregular terrain. In the previous study on the path planning problem of mobile robots, it has been usually focused on the collision-free path planning for wheeled robots. The path planning problem of legged roboth, however, has unique aspects from the point of viw that the legged robot can cross over the obstacles and the gait constraint should be considered in the process of planning a path. To resolve this unique problem systematically, a new concept of the artificial intensity field of light is numerically constructed over the configuration space of the robot including the transformed obstacles and a feasible path is sought in the field. Also, the efficiency of the proposed method is shown by various simulation results.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.1
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• pp.56-62
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• 2011

Terrain recognition ability is crucial to the performance of legged robots in an outdoor environment. For instance, a robot will not easily walk and it will tumble or deviate from its path if there is no information on whether the walking surface is flat, rugged, tough, and slippery. In this study, the ground surface recognition ability of robots is discussed, and to enable walking robots to recognize the surface state and changes, a central moment method was used. The values of the sensor signals (load cell) of robots while walking were detected in the supported section and were analyzed according to signal variance, skewness, and kurtosis. Based on the results of such analysis, the surface state was detected and classified.