KwangWoong Yang

An Effective Kalman Filter Localization Method for Mobile Robots

An effective Kalman filter localization method for mobile robots is investigated in terms of the robust Kalman filter with perturbation estimator. In the recursive algorithm, the perturbation estimator produces equivalent perturbations with respect to the nominal state equation and the action model of a mobile robot is adaptively modified with the perturbation estimates. The integral control property of the perturbation estimator enables a great reduction of the localization error, specifically when the odometric disturbance is large. The Kalman filter recursive equations including predictor, corrector, perturbation estimator, and the corresponding covariance propagation equations are formulated systematically. The effectiveness of the proposed scheme is verified through simulation and experimental results for a wheeled mobile robot

Development of Dynamically Reconfigurable Personal robot

Architecture and method for accelerating the development of personal robots are presented. It includes the technology such as modularization with its own processing and standardization open to other developers. We mainly focus on the effective ways for integrating the various robotic components and interfacing among them. The architecture is implemented by developing the fully modularized personal robot DRP I (Dynamically Reconfigurable Personal robot). Its hardware component is easily attached to and detached from the whole system but also each software of the components is functionally distributed. As methodology for interfacing and integration of DRP I, we introduce Module-D (Module of DRP I) characterized functionally, VM-D (Virtual Machine of DRP I) and RPL(Robot Programming Languages) for supporting compatibility of each Module-D. As experimental work, the dynamically reconfigurable feature of the robot is introduced.

Robust mobile robot localization with combined Kalman filter-perturbation estimator

In this paper, a robust localization method for mobile robot based on the combination of Kalman filter and perturbation estimator is presented. It remarkably enhances the robustness of localization performance, specifically when large odometric errors are occurred. The perturbation estimator in the combined Kalman filter (CKF) is to estimate systematic errors which perturbs the behavior of nominal state transition equation. Intrinsically, it has the property of integrating the innovation, i.e., the difference between measurement and predicted measurement and thus gives a chance of more reducing the gap between real states and their estimates. After formulation of the CKF recursion, we show how the design parameters can be determined and how much beneficial it is through simulation and experiment for a two-wheeled mobile robot under indoor GPS.

Flexible docking mechanism using combination of magnetic force with error-compensation capability

An auto-recharging system for a mobile robot can help the robot to perform its tasks constantly and without human intervention. For implementing the system, a docking mechanism is required. This paper presents a new docking mechanism with a localization error-compensation capability. The proposed mechanism uses the combination of mechanical structure and magnetic forces between the docking connectors. It is a structure to improve the allowance ranges of lateral and directional docking errors, in which the robot is able to dock into the docking station. Consequently, this mechanism reduces dependency of a robot control and allows easy docking with only mechanical configuration. In this paper, the superiority of the proposed mechanism is verified with experimental results.

Development of 1-axis torque sensor with different shape of support and measurement spoke

This paper describes the design of a new 1-axis torque sensor that consists of two different type spokes. The sensor has three trapezoidal shape spokes and three support spokes. It serves a double purpose that the sensitivity and stiffness for driving torque. We suggest trapezoid-typed spokes rather than conventional rectangular-typed spoke for sensitivity, and support spokes are used to tolerate to decrease the deformation. The sensor is verified by finite element model analysis and experiments. The result showed the linear relationship between the applied weight and the measured value.

Study of motor arbiter for a human-like robot

In development of a human-like robot, a motor control has to manage many motors simultaneously. This paper proposes the method of motor control which makes the human-like robot have facial expressions and behaviors similar to a human. It applied the behavior-based control and motor arbiter for performing continuous behaviors by synthesizing unit behaviors of an upper body and a facial expression. The behavior-based control selects the proper behavior and facial expression about a sensor input of a robot and an output of a high task. The motor arbiter exists between the behavior and the motor driver, and arbitrates interfered outputs generated from when one or more behaviors are executed concurrently. The behavior and facial expression of the human-like robot are expressive of smooth and continuous behaviors by using the behavior-based control and motor arbiter which synthesize several unit behaviors.