JamTac: A Tactile Jamming Gripper for Searching and Grasping in Low-Visibility Environments.

Humans can feel and grasp efficiently in the dark through tactile feedback, whereas it is still a challenging task for robots. In this research, we create a novel soft gripper named JamTac, which has high-resolution tactile perception, a large detection surface, and integrated sensing-grasping capability that can search and grasp in low-visibility environments. The gripper combines granular jamming and visuotactile perception technologies. Using the principle of refractive index matching, a refraction-free liquid-particle rationing scheme is developed, which makes the gripper itself to be an excellent tactile sensor without breaking its original grasping capability. We simultaneously acquire color and depth information inside the gripper, making it possible to sense the shape, texture, hardness, and contact force with high resolution. Experimental results demonstrate that JamTac can be a promising tool to search and grasp in situations when vision is not available.

[1]  Georg Martius,et al.  A soft thumb-sized vision-based sensor with accurate all-round force perception , 2021, Nature Machine Intelligence.

[2]  Xiangyang Zhu,et al.  A soft neuroprosthetic hand providing simultaneous myoelectric control and tactile feedback , 2021, Nature Biomedical Engineering.

[3]  Lorenz Wellhausen,et al.  Learning quadrupedal locomotion over challenging terrain , 2020, Science Robotics.

[4]  David Howard,et al.  A Review of Jamming Actuation in Soft Robotics , 2020, Actuators.

[5]  Monica Malvezzi,et al.  Compliant gripper design, prototyping, and modeling using screw theory formulation , 2020, Int. J. Robotics Res..

[6]  Haodong Zhu,et al.  Universal SMP gripper with massive and selective capabilities for multiscaled, arbitrarily shaped objects , 2020, Science Advances.

[7]  Yongsheng Zhao,et al.  High-Load Soft Grippers Based on Bionic Winding Effect. , 2019, Soft robotics.

[8]  Fumiya Iida,et al.  Tactile Sensing Applied to the Universal Gripper Using Conductive Thermoplastic Elastomer. , 2018, Soft robotics.

[9]  Gang Liu,et al.  A skin-inspired tactile sensor for smart prosthetics , 2018, Science Robotics.

[10]  Jakub W. Pachocki,et al.  Learning dexterous in-hand manipulation , 2018, Int. J. Robotics Res..

[11]  Jean-Sébastien Plante,et al.  Sleeved Bending Actuators for Soft Grippers: A Durable Solution for High Force-to-Weight Applications , 2018, Actuators.

[12]  N. Lepora,et al.  The TacTip Family: Soft Optical Tactile Sensors with 3D-Printed Biomimetic Morphologies , 2018, Soft robotics.

[13]  Stephen Licht,et al.  Stronger at Depth: Jamming Grippers as Deep Sea Sampling Tools. , 2017, Soft robotics.

[14]  Edward H. Adelson,et al.  GelSight: High-Resolution Robot Tactile Sensors for Estimating Geometry and Force , 2017, Sensors.

[15]  Z. Jane Wang,et al.  Novel Tactile Sensor Technology and Smart Tactile Sensing Systems: A Review , 2017, Sensors.

[16]  Xiaokang Hu,et al.  A highly flexible and sensitive piezoresistive sensor based on MXene with greatly changed interlayer distances , 2017, Nature Communications.

[17]  S. Nefti-Meziani,et al.  Design of a Variable Stiffness Soft Dexterous Gripper , 2017, Soft robotics.

[18]  Kevin O'Brien,et al.  Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides , 2016, Science Robotics.

[19]  Hong Liu,et al.  Robot grasp detection using multimodal deep convolutional neural networks , 2016 .

[20]  Xuewen Wang,et al.  Flexible Capacitive Tactile Sensor Based on Micropatterned Dielectric Layer. , 2016, Small.

[21]  Vincent Hayward,et al.  Haptic Edge Detection Through Shear , 2016, Scientific Reports.

[22]  Robert J. Wood,et al.  Soft Robotic Grippers for Biological Sampling on Deep Reefs , 2016, Soft robotics.

[23]  CianchettiMatteo,et al.  A Bioinspired Soft Robotic Gripper for Adaptable and Effective Grasping , 2015 .

[24]  Yu Sun,et al.  Robot grasp planning based on demonstrated grasp strategies , 2015, Int. J. Robotics Res..

[25]  G. De Maria,et al.  Force/tactile sensor for robotic applications , 2012 .

[26]  Heinrich M. Jaeger,et al.  Universal robotic gripper based on the jamming of granular material , 2010, Proceedings of the National Academy of Sciences.

[27]  J. Randall Flanagan,et al.  Coding and use of tactile signals from the fingertips in object manipulation tasks , 2009, Nature Reviews Neuroscience.

[28]  Nadia Cheng,et al.  Soft Robotics Commercialization: Jamming Grippers from Research to Product. , 2016, Soft robotics.