Hyong-Euk Lee

Human-machine interface for wheelchair control with EMG and its evaluation

The objective of this paper is to develop a powered wheelchair controller based on EMG for users with high-level spinal cord injury. EMG is very naturally measured when the user indicating a certain direction and the force information which will be used for the speed of wheelchair is easily extracted from EMG. Furthermore, the emergency situation based on EMG will be checked relatively ease. We classified the pre-defined motions such as rest case, forward movement, left movement, and right movement by fuzzy min-max neural networks (FMMNN). This classification results and evaluation results with real users shows the feasibility of EMG as an input interface for powered wheelchair.

Effective learning system techniques for human-robot interaction in service environment

HRI (Human-Robot Interaction) is often frequent and intense in assistive service environment and it is known that realizing human-friendly interaction is a very difficult task because of human presence as a subsystem of the interaction process. After briefly discussing typical HRI models and characteristics of human, we point out that learning aspect would play an important role for designing the interaction process of the human-in-the loop system. We then show that the soft computing toolbox approach, especially with fuzzy set-based learning techniques, can be effectively adopted for modeling human behavior patterns as well as for processing human bio-signals including facial expressions, hand/ body gestures, EMG and so forth. Two project works are briefly described to illustrate how the fuzzy logic-based learning techniques and the soft computing toolbox approach are successfully applied for human-friendly HRI systems. Next, we observe that probabilistic fuzzy rules can handle inconsistent data patterns originated from human, and show that combination of fuzzy logic, fuzzy clustering, and probabilistic reasoning in a single frame leads to an algorithm of iterative fuzzy clustering with supervision. Further, we discuss a possibility of using the algorithm for inductively constructing probabilistic fuzzy rule base in a learning system of a smart home. Finally, we propose a life-long learning system architecture for the HRI type of human-in-the-loop systems.

Iterative Fuzzy Clustering Algorithm With Supervision to Construct Probabilistic Fuzzy Rule Base From Numerical Data

To deal with data patterns with linguistic ambiguity and with probabilistic uncertainty in a single framework, we construct an interpretable probabilistic fuzzy rule-based system that requires less human intervention and less prior knowledge than other state of the art methods. Specifically, we present a new iterative fuzzy clustering algorithm that incorporates a supervisory scheme into an unsupervised fuzzy clustering process. The learning process starts in a fully unsupervised manner using fuzzy c-means (FCM) clustering algorithm and a cluster validity criterion, and then gradually constructs meaningful fuzzy partitions over the input space. The corresponding fuzzy rules with probabilities are obtained through an iterative learning process of selecting clusters with supervisory guidance based on the notions of cluster-pureness and class-separability. The proposed algorithm is tested first with synthetic data sets and benchmark data sets from the UCI Repository of Machine Learning Database and then, with real facial expression data and TV viewing data.

Automatic Generation of Conversational Robot Gestures for Human-friendly Steward Robot

Recently, in service robotics area, increasing attention is being paid on interaction capability of robot for human-being as well as its task performing capability. In this paper, in particular, an automatic gesture generation methodology for conversational interaction of service robots is presented toward more human-friendly human-robot interaction. From the survey on the results in the psychology field, we first categorized the target gestures into the three types of gestures, which are basic, supplementary/emphasizing, and finishing/interconnective gestures with their corresponding unit gesture components. Then, a set of mapping rules have been extracted for gesture generation based on observing human behavioral patterns during conversation, by means of morpheme decomposition and analysis. From the given text input in Korean, the proposed system tries to generate robotic gestures, which consist of the head and the arm motions, by gesture selection and motion scheduling schemes. Finally, we discuss on the effectiveness of the proposed system with the simulated motions of robot as an initial attempt to apply in a practical system.

Development of a steward robot for human-friendly interaction

Independence of people in need in their living environment becomes an imperative notion for any society in the years to come. As an approach to achieve independence, this paper addresses the problem of controlling an assistive home environment emphasizing a human-friendly man-machine interaction. We introduce a new service robot, named Joy, which can be categorized as a steward robot. As an intermediate agent between inhabitants and a complex smart house environment, this robot can provide the users with easily accessible, convenient, and cost effective environment for independent living. The learning capability and emotional interaction of the robot can enhance human-friendliness in various tasks. A learning system can provide personalized services by accumulating knowledge of the behavior patterns of the user in daily activities. An emotional interaction system generates facial expressions to be more human-friendly. We have developed two types of steward robots: a software type and hardware type. The hardware-type robot has a mobile platform and two robotic arms to perform various tasks with mobility.

Realization and Evaluation of Assistive Human-Mechatronic Systems with Human-friendly Robotic Agents at HWRS-ERC

Three types of assistive human-mechatronic systems are considered: (1) a smart house system for the elderly/the disabled, (2) a factory environment for the elderly/the disabled, and (3) a hospital surgery room for medical doctors. We report how each of these systems have been implemented with human-friendly robotic agents and what have been modified with feedback evaluation of the potential users during the course of our last 9 year projects at HWRS-ERC. Special attention will be given to the aspect of human-friendly human-machine interaction and to the task-oriented design (TOD) principle. With regard to more difficult problems to resolve than the solutions that we have achieved by far, we shall further discuss some of the important prospects and issues of future development, including safety and long-term learning, in the area of assistive service robotic system technology for people in need such as the elderly and the disabled for their independence and pride so as to enhance quality of life and possibly endow capability to do proper productive work.

Steward Robot: Emotional Agent for Subtle Human-Robot Interaction

In this paper, we propose a new service agent, called a steward robot, which provides inhabitants with accessible, convenient, and cost effective interfaces as an intermediate agent between the user and a smart home environment. To implement more subtle emotional reaction of the agent, we adopt a novel emotional cue, sentiment relation, and address a problem of modeling the intensity and transition of emotion words, while previous researches have mainly focused on the selection of discrete emotion words from psychological point of view. We also discuss some issues of the proposed emotional model applying a virtual scenario to our Intelligent Sweet Home

Multi sensors-based approach for intention reading with soft computing techniques

Humans intention plays a key role in human-machine interaction as in the case of a robot serving for a handicapped person. The quality of a service robot will be much enhanced if the robot can infer the humans intension during the interaction process. In this paper, we propose a soft computing-based technique to read a users intention using some multisensors-based approach. We have tested the technique by a scenario of serving a drink to the user. With such force/torque or vision sensor, the robot can effectively infer the users intention to drink the beverage or not to drink. As an application, this intention technique is employed for building a rehabilitation robot, called KARES II, to perform various human-friendly human-robot interaction.

A Steward Robot to Help Daily Activities in a Smart House Environment

Independence of the people in need in their activities of daily living becomes a matter of vital importance to any society in the years to come. As an approach to achieve independence, this paper addresses the problem of controlling assistive home environment emphasizing human-friendly human-machine interaction. To provide inhabitants with easily accessible, convenient, and cost-effective environment for independent living, we introduce a new service robot categorized into a steward robot as an intermediate agent between inhabitants and complex smart house environment. The learning capability and emotional interaction of the robot can enhance human-friendliness in various tasks. A learning system enables the robot to provide customized services by accumulating knowledge of the users behavior patterns in daily activities. An emotional interaction system generates facial expressions to communicate with the user in a human-friendly manner. We have developed two types of steward robots: a software type to use everywhere by personal computing devices such as a PDA and a cellular phone, and a hardware type to provide tangible services with physical interaction by two robotic arms and a mobile base.

LEARNING TECHNIQUES IN SERVICE ROBOTIC ENVIRONMENT

This presentation addresses the problems of realizing human-friendly man-machine interaction in service robotic environment with emphasis on learning capability. After briefly reviewing the issues of human-robot interaction and various learning techniques from engineering point of view, we report our experiences in case studies where some learning techniques are successfully implemented in service robotic environment and discuss open issues of learning systems such as adaptivity and life-long learning capability.