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Abstract The mechanoreceptors of the human tactile sensory system contribute to natural grasping manipulations in everyday life. However, in the case of robot systems, attempts to emulate humans’ dexterity are still limited by tactile sensory feedback. In this work, a soft optical lightguide is applied as an afferent nerve fiber in a tactile sensory system. A skin‐like soft silicone material is combined with a bristle friction model, which is capable of fast and easy fabrication. Due to this novel design, the soft sensor can provide not only normal force (up to 5 Newtons) but also lateral force information generated by stick‐slip processes. Through a static force test and slip motion test, its ability to measure normal forces and to detect stick‐slip events is demonstrated. Finally, using a robotic gripper, real‐time control applications are investigated where the sensor helps the gripper apply sufficient force to grasp objects without slipping.
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Inter-finger Small Object Manipulation With DenseTact Optical Tactile Sensor
The ability to grasp and manipulate small objects in cluttered environments remains a significant challenge. This letter introduces a novel approach that utilizes a tactile sensor-equipped gripper with eight degrees of freedom to overcome these limitations. We employ DenseTact 2.0 for the gripper, enabling precise control and improved grasp success rates, particularly for small objects ranging from 5 mm to 25 mm. Our integrated strategy incorporates the robot arm, gripper, and sensor to manipulate and orient small objects for subsequent classification, effectively. We contribute a specialized dataset designed for classifying these objects based on tactile sensor output and a new control algorithm for in-hand orientation tasks. Our system demonstrates 88% of successful grasp and successfully classified small objects in cluttered scenarios.
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- PAR ID:
- 10523012
- Publisher / Repository:
- IEEE Robotics and Automation Letters
- Date Published:
- Journal Name:
- IEEE Robotics and Automation Letters
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2377-3774
- Page Range / eLocation ID:
- 515 to 522
- Subject(s) / Keyword(s):
- Dexterous Manipulation in-hand manipulation grasping
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/LRA.2023.3333735
