TY - GEN
T1 - Sensory-motor augmentation of the robot with shared human perception
AU - Ishida, Ryuya
AU - Meli, Leonardo
AU - Tanaka, Yoshihiro
AU - Minamizawa, Kouta
AU - Prattichizzo, Domenico
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/27
Y1 - 2018/12/27
N2 - Robots have replaced people in many manufacturing production lines but the information they gather from sensors might not be sufficient to autonomously accomplish dexterous manipulation operations. Symbiotic human-robot cooperation appears to be a more realistic near future in industrial scenarios. In this paper we present a configuration of human-robot collaboration in which the robot is sensory-augmented by means of a set of tactile signals coming from the human operator. The incorporation of low-level robot 'intelligence' permits the cooperative manipulation of an object while enabling the human operator to stay focused on task itself and carry it out in the most natural way. The effectiveness of this approach is demonstrated in a use case in which a robot helps a human operator to successfully accomplish a writing task. System performance has been evaluated, considering several positions of the tiny vibration sensor in charge of gathering the human perception, by testing it on both the human hand and the co-manipulated object. Results suggest that the sensor provides valuable information for recognizing operator actions when it is placed either on the human hand or on the co-manipulated object. However, the sensor on the finger directly represents the operator's perception, while the output of the sensor attached to the object changes according to the distance between the interaction point and the sensor itself. In addition, in wearing the sensor, neither the object nor the robot need to be instrumented: the operator is free to interact with a large set of objects and collaborate with any existing robot without requiring supplemental equipment.
AB - Robots have replaced people in many manufacturing production lines but the information they gather from sensors might not be sufficient to autonomously accomplish dexterous manipulation operations. Symbiotic human-robot cooperation appears to be a more realistic near future in industrial scenarios. In this paper we present a configuration of human-robot collaboration in which the robot is sensory-augmented by means of a set of tactile signals coming from the human operator. The incorporation of low-level robot 'intelligence' permits the cooperative manipulation of an object while enabling the human operator to stay focused on task itself and carry it out in the most natural way. The effectiveness of this approach is demonstrated in a use case in which a robot helps a human operator to successfully accomplish a writing task. System performance has been evaluated, considering several positions of the tiny vibration sensor in charge of gathering the human perception, by testing it on both the human hand and the co-manipulated object. Results suggest that the sensor provides valuable information for recognizing operator actions when it is placed either on the human hand or on the co-manipulated object. However, the sensor on the finger directly represents the operator's perception, while the output of the sensor attached to the object changes according to the distance between the interaction point and the sensor itself. In addition, in wearing the sensor, neither the object nor the robot need to be instrumented: the operator is free to interact with a large set of objects and collaborate with any existing robot without requiring supplemental equipment.
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U2 - 10.1109/IROS.2018.8594496
DO - 10.1109/IROS.2018.8594496
M3 - Conference contribution
AN - SCOPUS:85062943768
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 2596
EP - 2603
BT - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
Y2 - 1 October 2018 through 5 October 2018
ER -