• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.301-307
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• 2011

Based on the stability criteria of ZMP (Zero Moment Point), this paper proposes an adjusting algorithm that modifies walking trajectory of a bipedal robot for stable walking by analyzing ZMP trajectory of it. In order to maintain walking balance of the bipedal robot, ZMP should be located within a supporting polygon that is determined by the foot supporting area with stability margin. Initially tilting imposed to the trajectory of the upper body is proposed to transfer ZMP of the given walking trajectory into the stable region for the minimum stability. A neural network method is also proposed for the stable walking trajectory of the biped robot. It uses backpropagation learning with angles and angular velocities of all joints with tilting to get the improved walking trajectory. By applying the optimized walking trajectory that is obtained with the neural network model, the ZMP trajectory of the bipedal robot is certainly located within a stable area of the supporting polygon. Experimental results show that the optimally learned trajectory with neural network gives more stability even though the tilting of the pelvic joint has a great role for walking stability.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.375-377
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• 2009

This paper researched the algorithm of robot's walking and action on the basis of robot studied and made at our laboratory and studied how to efficiently control the robot joints by developing wireless Digital Servo Motor using Zigbee Sensor Network Module which is using at wide part recently. I realized the stable walking by adopt Press Sensor at the bottom of robot foot to get stability of walking. Also I let the algorithm calculate the robot movement to make the joint motion and monitored the robot walk to its motion. At this Paper, I studied the method organizing the motion by the each robot walking and measuring the torque applying to the joint. And I also knew that it is possible to make its control and construct hardware more conveniently than them of the existing studied and controling 2Legs Walking Robot by applying it at walking robot and developing wireless servo motor by Zirbee Sensor Network.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.963-968
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• 2010

This paper handles ZMP based control that is inspired by neural networks for humanoid robot walking on varying sloped surfaces. Humanoid robots are currently one of the most exciting research topics in the field of robotics, and maintaining stability while they are standing, walking or moving is a key concern. To ensure a steady and smooth walking gait of such robots, a feedforward type of neural network architecture, trained by the back propagation algorithm is employed. The inputs and outputs of the neural network architecture are the ZMPx and ZMPy errors of the robot, and the x, y positions of the robot, respectively. The neural network developed allows the controller to generate the desired balance of the robot positions, resulting in a steady gait for the robot as it moves around on a flat floor, and when it is descending slope. In this paper, experiments of humanoid robot walking are carried out, in which the actual position data from a prototype robot are measured in real time situations, and fed into a neural network inspired controller designed for stable bipedal walking.

• Journal of the Korean Institute of Rural Architecture
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• v.23 no.1
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• pp.35-42
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• 2021

This study analyzed the path that affects the user's walking satisfaction on main street in four local government towns in Jeollanam-do. and as an empirical study to find the direction of improvement toward the main street from the perspective of walking, the results are as follows. First, it was found that the network had a direct (+) effect on walking satisfaction as a main street. In addition, it was analyzed that land use had no direct (+) effect on walking satisfaction on the main street, but had a direct (+) effect on the network. Second, it was analyzed from the fact that the walking environment does not have a direct (+) effect on walking satisfaction, but has a direct (+) effect on the network. and it was analyzed that the street-building relationship had a direct (+) effect on the street landscape, and the street landscape had a direct (+) effect on the walking environment. The study was completed by suggesting implications according to the above research results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.221-227
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• 2002

In this paper, the system model for the compensation of the low-cost personal navigation system is derived and the error compensation method using GPS is also proposed. WNS(Walking Navigation System) is a kind of personal navigation system using the number of a walk, stride and azimuth. Because the accuracy of these variables determines the navigation performance, computational methods have been investigated. The step is detected using the walking patterns, stride is determined by neural network and azimuth is calculated with gyro output. The neural network filters off unnecessary motions. However, the error compensation method is needed, because the error of navigation information increases with time. In this paper, the accumulated error due to the step detection error, stride error and gyro bias is compensated by the integrating with GPS. Loosely coupled Kalman filter is used for the integration of WNS and GPS. It is shown by simulation that the error is bounded even though GPS signal is blocked.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.95-97
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• 2005

This paper deals with the implementation of walking for a humanoid robot by ZMP measurement using wireless sensor network. ZMP is measured by FSR sensors which are mounted at each corner of a sole. The wireless sensor network collects the sensor data according and exchanges robot information between host PC and a robot system. The master controller mounted on robot body receives trajectory data from the host PC via sensor network and drives the joint motor based on trajectory data. The time scheduler of the master controller controls the events at the ratio of 100ms. With this configuration, the walking of the humanoid robot KHR-1 could be realized successfully.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2138-2142
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• 2005

A wearable sensor system is proposed as a man-machine interface to control a device for walking assistance. The sensor system is composed of small sensors to detect the information about the user's body motion such as the activity level of skeletal muscles and the acceleration of each body parts. Each sensor includes a microcomputer and all the sensors are connected into a network by using the serial communication function of the microcomputer. The whole network is integrated into a belt made of soft fabric, thus, users can put on/off very easily. The sensor system is very reliable because of its decentralized network configuration. The body information obtained from the sensor system is used for controlling the assisting device to achieve a comfortable and an effective walking training.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.95-103
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• 2018

This study set out to evaluate the fitness of shelter locations by taking into consideration service zones according to walking speed, the changing population between day and night, and walking routes. Walking speed was defined as 1.6 m/s, 2 m/s based on the cases of previous studies. The changing population between day and night was estimated with the dasymetric mapping technique. Shelter service zones according to walking speed and routes were analyzed with the network of the location allocation model. The findings show some shelters had limits with their capacity according to the changing floating population and walking speed in time and space and raise a need to appoint additional shelters.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1081-1087
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• 2006

Generally, biped walking is difficult to control because a biped robot is a nonlinear system with various uncertainties. In this paper, we propose a hybrid sliding-mode control method using a WNN uncertainty observer for stable walking of the 5-link biped robot with model uncertainties and the external disturbance. In our control system, the sliding mode control is used as main controller for the stable walking and a wavelet neural network(WNN) is used as an uncertainty observe. to estimate uncertainties of a biped robot model, and the error compensator is designed to compensate the reconstruction error of the WNN. The weights of WNN are trained by adaptation laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified through computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.530-537
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• 2009

A graphic simulator can be a useful tool for planning gaits or dynamic behaviors to a walking pet robot. Microsoft describes robotics developer studio (MSRDS) as an end-to-end robotics development platform including simulation engine based on dynamics. In this paper, we propose a pet robot simulator (PRS), based on MSRDS, which supports interactively controlled two walking robots connected over network. To be pet robot simulator, modeling a commercial pet robot is performed and gait planning is also implemented. By using concurrency and coordination runtime (CCR) and decentralized software services (DSS) of MSRDS software platform, we connect two robots which are displayed together but controlled separately over network. The two walking pet robots can be simulated interactively by joysticks. It seems to be an internet game for pet robots.