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Real-Time Collision Detection Based On One Class Svm For Safe Movement Of Humanoid Robot

2017 IEEE-RAS 17TH INTERNATIONAL CONFERENCE ON HUMANOID ROBOTICS (HUMANOIDS)(2017)

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摘要
In this paper, a new real-time collision detection method based on the one class support vector machine method for the safe movement of humanoid robots is proposed. To generate a representational model for collision detection requires only normal movement data and does not require collision data which is not easy to obtain. With this method, a real-time emergency stop function for humanoid robots is activated during collisions while walking quadruped. It is important for the operator who operates the robot remotely to be able to interpret collision information properly. To support the operator with information to understand situations, localization of a collision point is also implemented with a multi class support vector machine method.
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关键词
class SVM,humanoid robot,real-time collision detection method,class support vector machine method,representational model,normal movement data,collision data,real-time emergency stop function,robot remotely,collision information,collision point,multiclass support vector machine method,real-time collision detection
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