Title :
Blind collision detection and obstacle characterisation using a compliant robotic arm
Author :
Wisanuvej, Piyamate ; Jindong Liu ; Ching-Mei Chen ; Guang-Zhong Yang
Author_Institution :
Hamlyn Centre for Robotic Surg., Imperial Coll. London, London, UK
fDate :
May 31 2014-June 7 2014
Abstract :
This paper presents a novel blind collision detection and material characterisation scheme for a compliant robotic arm. By the incorporation of a simple MEMS accelerometer at each joint, the robot is able to detect collision, identify the material of an obstacle, and create a map of the environment. Detailed hardware design is provided, illustrating its value for building a compact and economical robot platform. The proposed method does not require the additional use of vision sensor for mapping the environment, and hence is termed as `blind´ collision detection and environment mapping. Based on the shock wave and vibration signals, the proposed algorithm is able to classify a range of materials encountered. Detailed laboratory evaluation was performed with controlled obstacle collision from different orientation and locations with varying force and materials. The proposed method has achieved 98% detection sensitivity while maintaining 77% specificity. Furthermore, by using sound feature extraction and machine learning techniques, the classifier produces an accuracy of 98% for classifying four different impact materials. In this paper, we also demonstrate its use for detailed environment mapping by using the proposed method.
Keywords :
accelerometers; collision avoidance; feature extraction; force control; image sensors; learning (artificial intelligence); microsensors; robot vision; MEMS accelerometer; blind collision detection; compliant robotic arm; economical robot platform; environment mapping; hardware design; machine learning; obstacle characterisation; shock wave; sound feature extraction; vibration signals; vision sensor; Acceleration; Collision avoidance; Joints; Materials; Robot sensing systems; Vibrations;
Conference_Titel :
Robotics and Automation (ICRA), 2014 IEEE International Conference on
Conference_Location :
Hong Kong
DOI :
10.1109/ICRA.2014.6907170