2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) 2012
DOI: 10.1109/aim.2012.6265986
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Human-robot cooperation for heavy object manipulation based on sensing pneumatic pressure in air cushions

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Cited by 3 publications
(2 citation statements)
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“…Abinaya et al also studied an air pressure sensor based smart shoes for gait monitoring and reported that the pressure changes in the air bladder are linearly proportional to the exerted force [ 30 ]. Nozawa et al proposed a method of sensing pneumatic pressure in air cushions for human-robot cooperative heavy object manipulation [ 31 ]. The air bladder as a sensing device possesses some noticeable advantages for co-operative applications: the air in the bladder is compressible, thus the air bladder is compliant and makes soft contact between the human and the robot.…”
Section: Introductionmentioning
confidence: 99%
“…Abinaya et al also studied an air pressure sensor based smart shoes for gait monitoring and reported that the pressure changes in the air bladder are linearly proportional to the exerted force [ 30 ]. Nozawa et al proposed a method of sensing pneumatic pressure in air cushions for human-robot cooperative heavy object manipulation [ 31 ]. The air bladder as a sensing device possesses some noticeable advantages for co-operative applications: the air in the bladder is compressible, thus the air bladder is compliant and makes soft contact between the human and the robot.…”
Section: Introductionmentioning
confidence: 99%
“…It was not until 2014 the number of human-focused papers started matching the number of technical papers. This suggests either an increase in interest in the one or two years leading up to this point or that the technological or ethical requirements for safe SHRC had been met to a wider [34,40,48,85,90,92] Pressure sensors [78,101,116] Projected Augmented Reality [49,70,72] Robot-mounted controller [8,9,28] Visual interfaces [82,83] Audio interfaces [82] Tactile sensors [7] Probabilistic state machine 18 [3, 11, 16, 22, 30, 40, 42, 62, 64-66, 68, 72, 96, 98, 108-110] Machine learning 13 [15,33,39,46,51,56,85,89,99,103,113,121,124] Speech recognition 11 [13,17,41,46,57,69,80,94,102,106,123] Gesture recognition [25,90,94] Multi-robot coordination…”
Section: Research Trendsmentioning
confidence: 99%