Browsing by Author "Lin, Chia-How"

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A New Design on Multi-Modal Robotic Focus Attention
(2008)
Lin, Chia-How
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Yang, Chia-Hsing
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Wang, Cheng-Kang
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Song, Kai-Tai
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Hu, Jwu-Sheng
Human detection and tracking is important for user-friendly human-robot interaction. The robot should be able to find the user autonomously and keep its attention to the user in a human-like manner. In this paper, a design and experimental study of robust human detection and tracking is presented through fusion several modalities of sensory information. The multi-modal interaction design utilizes a combination of visual, audio, and laser scanner data for reliable detection and tracking of an interested user. During tracking motion, obstacle avoidance behavior will be activated any time required to ensure safety. Furthermore, user can further assign the robot to interact with other user by speech command. Experimental results show that the robot can robustly tracks person under complex scenarios.
AN INTERACTIVE CONTROL ARCHITECTURE FOR MOBILE ROBOTS
(2013)
Lin, Chia-How
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Song, Kai-Tai
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電子工程學系及電子研究所
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電控工程研究所
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交大研究總中心
Programming a robot to handle daily-life tasks in a dynamic changing environment with versatile and responsive behaviours is challenging. An intelligent robot needs to integrate many heterogeneous modules of various features using a powerful control architecture. This study aims to develop a methodology for designing a flexible real-time robot control system using an agent-based approach. The proposed control architecture decomposes a complex robotic control system into agents and allows heterogeneous modules to he integrated more efficiently. The software framework solves resource sharing, message flow and coding problems, and helps to integrate separate processes into a whole system with less effort. The proposed core components guarantee real-time response and high performance of the robotic system. This approach is also suitable for system integration of a research team, where the software modules from different, developers can be integrated on the robot and teamwork can he realized much easier. Interesting experiments on robotic focus attention and human robot interaction using two laboratory-developed robots demonstrate the effectiveness of the proposed control architecture.
Autonomous Emotional Expression Generation of a Robotic Face
(2009)
Han, Meng-Ju
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Lin, Chia-How
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Song, Kai-Tai
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電控工程研究所
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Institute of Electrical and Control Engineering
This paper presents a novel design of autonomous robotic facial expression generation using a fuzzy-neuro network. The emotional characteristics of a robot can be specified in this design by assigning weights in the fuzzy-neuro network. The robotic face generates appropriate expressions in responding to the image recognition results of a user's emotional state and the assigned robotic emotional characteristics. In this study, two contrast emotional characteristics, optimistic and pessimistic, have been designed and tested to verify their responses to the recognized user emotional states (neutral, happiness, sadness and anger). Computer simulations of a robotic face show that the proposed facial expression generation system effectively responds to a user's emotional states in a human-like manner by fusing outputs of four facial expressions (boring, happiness, sadness and surprise).
Location Estimation Using Probability Map of a ZigBee Sensor Network
(2013)
Lin, Chia-How
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Song, Kai-Tai
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電控工程研究所
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Institute of Electrical and Control Engineering
For an on-demand robotic system, the location aware module works to provide location information of interested objects and mobile robots. This information supports various intelligent behaviors of a service robot. In this paper, a novel probability-based approach to building up a location aware system is presented. In this approach, the uncertainties and inconsistency normally suffered from received signal strength indicator (RSSI) measurements are handled with minimum prior calibration effort. By taking merely one off-line calibration measurement in a ZigBee sensor network, the inherent problem of signal uncertainty of to-be-localized nodes can be effectively resolved. The proposed RSSI-based algorithm thus has the flexibility in the thus has the flexibility in deployment of sensor nodes in various environments. The proposed algorithm has been verified in several typical environments. Comparison experiments show that the method outperforms existent algorithms in different environments.
Mobile Manipulation and Visual Servoing Design of a Configurable Mobile Manipulator
(2013-01-01)
Song, Kai-Tai
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Jiang, Sin-Yi
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Wu, Ching-Jui
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Lin, Ming-Han
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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.
Mobile Robot Intruder Detection Based on a Zigbee Sensor Network
(2008)
Lin, Chia-How
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Yang, Su-Hen
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Chen, Hong-Tze
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Song, Kai-Tai
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電控工程研究所
This paper presents an intruder detection system, which consists of a Zigbee sensor network and an autonomous mobile robot Multiple Zigbee sensor modules installed in the environment can detect intruders and abnormal conditions. Sensor nodes transmit intrusion alarm to the monitoring center as well as the mobile robot via Zigbee wireless mesh network. The robot can navigate in the environment autonomously and approach to a target place using onboard localization system. If any possible intruder is detected, the robot immediately moves to that location and transmits images to remote mobile devices such as PDA or smart phone of security guards and users, in order to determine and response to the situation in real time.
Probability-Based Location Aware Design and On-Demand Robotic Intrusion Detection System
(2014-06-01)
Lin, Chia-How
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Song, Kai-Tai
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電控工程研究所
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Institute of Electrical and Control Engineering
For an on-demand robotic system, a location aware module provides location information of objects, users, and the mobile robot itself. This information supports various intelligent behaviors of a service robot in day-to-day scenarios. This paper presents a novel probability-based approach to building a location aware system. With this approach, the inconsistencies often seen in received signal strength indicator (RSSI) measurements are handled with a minimum of calibration. By taking off-line calibration measurement of a ZigBee sensor network, the inherent problem of signal uncertainty of to-be-localized nodes can be effectively resolved. The proposed RSSI-based algorithm allows flexible deployment of sensor nodes in various environments. The proposed algorithm has been verified in several typical environments and experiments show that the method outperforms existing algorithms. The location aware system has been integrated with an autonomous mobile robot to demonstrate the proposed on-demand robotic intruder detection system. In the experiments, three alarm sensors were employed to monitor abnormal conditions. If an intrusion was detected, the robot immediately moves to the location and transmits scene images to the user, allowing the user to respond to the situation in real time.
Robotic Emotional Expression Generation Based on Mood Transition and Personality Model
(2013-08-01)
Han, Meng-Ju
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Lin, Chia-How
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Song, Kai-Tai
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電機資訊學士班
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Undergraduate Honors Program of Electrical Engineering and Computer Science
This paper presents a method of mood transition design of a robot for autonomous emotional interaction with humans. A 2-D emotional model is proposed to combine robot emotion, mood, and personality in order to generate emotional expressions. In this design, the robot personality is programmed by adjusting the factors of the five factor model proposed by psychologists. From Big Five personality traits, the influence factors of robot mood transition are determined. Furthermore, a method to fuse basic robotic emotional behaviors is proposed in order to manifest robotic emotional states via continuous facial expressions. An artificial face on a screen is a way to provide a robot with a humanlike appearance, which might be useful for human-robot interaction. An artificial face simulator has been implemented to show the effectiveness of the proposed methods. Questionnaire surveys have been carried out to evaluate the effectiveness of the proposed method by observing robotic responses to a user's emotional expressions. Preliminary experimental results on a robotic head show that the proposed mood state transition scheme appropriately responds to a user's emotional changes in a continuous manner.
Robust Ground Plane Detection for Obstacle Avoidance of Mobile Robots Using a Monocular Camera
(2010)
Lin, Chia-How
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Jiang, Sin-Yi
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Pu, Yueh-Ju
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Song, Kai-Tai
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電控工程研究所
This paper presents a vision-based obstacle avoidance design using a monocular camera onboard a mobile robot. An image processing procedure is developed to estimate distances between the robot and obstacles based-on inverse perspective transformation (IPT) in image plane. A robust image processing solution is proposed to detect and segment navigatable ground plane area within the camera view. The proposed method integrate robust feature matching with adaptive color segmentation for plane estimation and tracking to cope with variations in illumination and camera view. After IPT and ground region segmentation, a result similar to the occupancy grid map is obtained for mobile robot obstacle avoidance and navigation. Practical experimental results of a wheeled mobile robot show that the proposed imaging system successfully estimates distance of objects and avoid obstacles in an indoor environment.
Robust ground plane region detection using multiple visual cues for obstacle avoidance of a mobile robot
(2015-02-01)
Lin, Chia-How
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Song, Kai-Tai
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電控工程研究所
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Institute of Electrical and Control Engineering
This paper presents a vision-based obstacle avoidance design using a monocular camera onboard a mobile robot. A novel image processing procedure is developed to estimate the distance between the robot and obstacles based-on inverse perspective transformation (IPT) in an image plane. A robust image processing solution is proposed to detect and segment a drivable ground area within the camera view. The proposed method integrates robust feature matching with adaptive color segmentation for plane estimation and tracking to cope with variations in illumination and camera view. After IPT and ground region segmentation, distance measurement results are obtained similar to those of a laser range finder for mobile robot obstacle avoidance and navigation. The merit of this algorithm is that the mobile robot can have the capacity of path finding and obstacle avoidance by using a single monocular camera. Practical experimental results on a wheeled mobile robot show that the proposed imaging system successfully obtains distances of surrounding objects for reactive navigation in an indoor environment.