tailieunhanh - Humanoid Robots Part 4

Tham khảo tài liệu 'humanoid robots part 4', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 68 Humanoid Robots b The robot applies rules see or examples see that have been previously acquired and performs an action. If there is no rule or example which should be applied the robot does not perform any action. c When the robot performs an action the user makes the judgment whether the performance is correct or not and if it is not the user teaches it the right action feedback process . After that the system adds a pair of input command and taught action to the example database. d If the humanoid robot does not perform any action the user teaches it a proper action by direct physical feedback see . Then the system adds a pair of command and action to the example database. e Finally the system generates rules which represent meanings of connectives from the example database by Three Examples Based Inductive Learning process see . Fig. 1. System overview Element of Action In their work on understanding of order expressions for actions Shinyama et al. discussed about the vagueness in instructions and the mistiness in spatial points Shinyama et al. 2001 . Regarding the vagueness in instructions robots have to determine whether a user s utterance instructs to perform something or not. Although for example can you raise your hand has a form of a question it may instruct the robot to raise its hand. Concerning the vagueness of spatial points robots have to determine where the point of the user s instruction is. For example raise your hand has vagueness of height which the hand should be raised In our previous work Hasegawa et al. 2007 to make the acquisition of connective simpler we defined an action as a body movement trajectory of the shortest distance between starting and final positions. The final position which the robot should reach is obtained from user s input. Furthermore we resolve the vagueness by teaching and averaging. The robot determines a final position of an action as an average point from all inputs taught by all users who

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