Browsing by Author "Liu, Chien-Hung"

Now showing 1 - 2 of 2

A New Approach to Map Joining for Depth-Augmented Visual SLAM
(2013)
Liu, Chien-Hung
;
Song, Kai-Tai
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, a novel scheme is proposed to improve real-time performance of simultaneous localization and mapping (SLAM) of a mobile robot based on depth-augmented visual features. In this design, the robot has two stages in navigation applications, namely the map building stage and the map usage stage. In the map-building stage, a local map is built to join into the global map. For the map-usage stage, instead of using the global map, the local maps facilitate real-time path tracking control of the robot. Using of local maps has the merit of reducing the computational complexity of EKF-SLAM. In the map joining procedure, deviations of adjacent local maps are corrected based on local features. Loop closure detection is used to determine whether the local map building is completed. A Kinect sensor is adopted to realize the proposed method. Navigation experiments on a wheeled mobile robot show that the motion error of robot localization is within 0.1m for a travel over 83m.
Mobile Manipulation and Visual Servoing Design of a Configurable Mobile Manipulator
(2013-01-01)
Song, Kai-Tai
;
Jiang, Sin-Yi
;
Wu, Ching-Jui
;
Lin, Ming-Han
;
Wu, Cheng Hei
This paper presents a mobile manipulation and visual servoing design for a configurable mobile manipulator by using a Kinect sensor. To achieve this goal, an image-based grasping design is combined with a visual simultaneous localization and mapping (vSLAM). The proposed vSLAM method is based on extended Kalman filter (EKF) and a Kinect RGBD sensor. In the manipulator design, the robot arms are designed to be able to configure as a handrail for user support in execution of walking assistance tasks. The purpose of this design is to perform mobile manipulation and walking assistance tasks on the same robot. Experiments on the prototype dual-arm mobile manipulator validate that the proposed method can find and grasp a target object after navigation a distance to the object position. After the robot delivered the object to the user, it configured to provide walking assist to the user using the suggested compliance controller.