User-machine interface system for enhanced interaction

A user recognition growth system, comprising:

• a behavior selection and determination structure for selecting and deciding behaviors based on user information;
• a user information recognition structure for recognizing a user;
• a memory structure for storing the recognized user information;
• a calculating structure for comparing the recognized user information with the stored user information to calculate user recognition;
• and
• a compensating structure for compensating a selection and determination method in the behavior selection and determination structure in accordance with the calculated user recognition.

A user recognition growth system, comprising:

• a behavior selection and determination structure for selecting and deciding behaviors based on user information;
• a user information recognition structure for recognizing a user;
• a memory structure for storing the recognized user information;
• a calculating structure for comparing the recognized user information with the stored user information to calculate user recognition;
• and
• a compensating structure for compensating behaviors selected by the behavior selection and determination structure in accordance with the calculated user recognition.

A tactile expression system in a robot, comprising:

• an actuator for driving a robot;
• a detection structure for detecting user information and environment information;
• a feelings generation structure for generating artificial feelings for a robot based on the detecting user and environment information;
• and
• a behavior determination structure for determining behaviors by the robot based on the generated artificial feelings, wherein the behavior determination structure controls the actuator so that a resistance acted on the robot may be changed on tactile information the user has applied to the robot.

A method of enhancing interaction between a user and a machine, said machine comprising (i) a sensor unit for detecting a user, (ii) a data processing unit for extracting features of the user under predetermined rules, (iii) a memory, (iv) a second sensor unit for detecting a user's action, (v) a behavior decision unit including a behavior decision algorithm programmed to select the machine's action when receiving designated signals, and (vi) an actuating unit for actuating the selected action, said method comprising the steps of:

• (a) detecting a user by the sensor unit, extracting features of the user by the data processing unit, and recording the features of the user in the memory;
• (b) interacting with the user, detecting the user's action by the second sensor unit, and saving the user's action in the memory in relation to the features of the user, wherein the machine behaves using the behavior decision unit and the actuating unit;
• (c) determining whether any user having features identical or similar to those of the user is of record in the memory, and if any, updating the features of the user of record by statistical processing, and recording the updated features of the user in the memory in relation to the user's action;
• and
• (d) modifying the behavior decision algorithm in accordance with the significance of probability of identifying the user based on the statistically processed features of the user, whereby outcome of the machine actuated by the actuating unit changes based on interaction between the user and the machine.

A method of enhancing interaction between a user and a machine, said machine comprising (i) a sensor unit for detecting a user's gestures associated with or without voice, (ii) a behavior library storing behavioral patterns in relation to causative signals, (iii) a memory, (iv) a behavior decision unit including a behavior decision algorithm programmed to select the machine's action from the behavior library when receiving designated signals, and (vi) an actuating unit for actuating the selected action, said method comprising the steps of:

• (a) sensing the user's gestures associated with or without voice by the sensing unit, and recording the sensed gestures in the memory in relation to designated signals causative of the gestures;
• (b) updating the behavior library if the gestures are not of record in the library, and accordingly modifying the behavior decision algorithm;
• (c) when receiving signals indicative of gestures, selecting gestures by the behavior decision unit using the behavior library;
• and
• (d) actuating the machine to perform the gestures by the actuating unit.

A method of enhancing interaction between a user and a machine, said machine comprising (i) a tactile sensor unit for detecting tactile signals when a user touches the machine, (ii) a second sensor unit for sensing signals causative of the tactile signals, (iii) a memory, (iv) a pseudo-emotion generation unit including an emotion generation algorithm programmed to generate pseudo-emotions when receiving designated signals, (v) a behavior decision unit including a behavior decision algorithm programmed to select the machine's action when receiving designated signals including outcome of the pseudo-emotion generation unit, and (vi) an actuating unit for actuating the selected action, said method comprising the steps of:

• (a) sensing the user's tactile input by the sensing unit;
• (b) generating pseudo-emotions based on the tactile input and designated signals causative of the tactile input;
• (c) selecting an action of the machine by the behavior decision unit based on the tactile input, the generated pseudo-emotions, and the signals causative of the tactile input;
• and
• (d) actuating the machine to perform the selected action by the actuating unit.