Sensorization of a Continuum Body Gripper for High Force and Delicate Object Grasping

The goal of achieving ‘universal grasping' where many objects can be handled with minimal control input is the focus of much research due to potential high impact applications ranging from grocery packing to recycling. However, many of the grippers developed suffer from limited sensing capabilities which can prevent handing of both heavy bulky items and also lightweight delicate objects which require fine control when grasping. Sensorizing such grippers is often challenging due to the highly deformable surfaces. We propose a novel sensing approach which uses highly flexible latex bladders. By measuring changes in the air pressure of the bladders, normal force and longitudinal strain can be measured. These sensors have been integrated into a ‘Magic Ball' origami gripper to provide both tactile and proprioceptive sensing. The sensors show reasonable sensitivity and repeatability, are durable and low-cost, and can be easily integrated into the gripper without affecting performance. When the sensors are used for classification, they enabled identification of 10 objects with over 90% accuracy, and also allow failure to be detected through slippage detection. A control algorithm has been developed which uses the sensor feedback to extend the capabilities of the gripper to include both delicate and strong grasping. It is shown that this closed loop controller enables delicate grasping of potato chips; 80% of those tested were grasped without damage.

[1]  Matteo Cianchetti,et al.  Soft Robotics: New Perspectives for Robot Bodyware and Control , 2014, Front. Bioeng. Biotechnol..

[2]  C. Majidi Soft Robotics: A Perspective—Current Trends and Prospects for the Future , 2014 .

[3]  MajidiCarmel,et al.  Soft Robotics: A Perspective—Current Trends and Prospects for the Future , 2014 .

[4]  Fangfang Zhang,et al.  A Gecko-Inspired Gripper with Controllable Adhesion , 2018, ICIRA.

[5]  Teck-Hou Teng,et al.  Automated Robot Picking System for E-Commerce Fulfillment Warehouse Application , 2015 .

[6]  Fumiya Iida,et al.  Soft Robotics: Challenges and Perspectives , 2011, FET.

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

[8]  Fumiya Iida,et al.  Soft Manipulators and Grippers: A Review , 2016, Front. Robot. AI.

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

[10]  Kyoungchul Kong,et al.  Design and fabrication of a soft three-axis force sensor based on radially symmetric pneumatic chambers , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[11]  Nigel H. Lovell,et al.  A review of tactile sensing technologies with applications in biomedical engineering , 2012 .

[12]  Fumiya Iida,et al.  Tack and deformation based sensorised gripping using conductive hot melt adhesive , 2018, 2018 IEEE International Conference on Soft Robotics (RoboSoft).

[13]  Claudio Melchiorri,et al.  Slip detection and control using tactile and force sensors , 2000 .

[14]  Massimo Totaro,et al.  Toward Perceptive Soft Robots: Progress and Challenges , 2018, Advanced science.

[15]  D. Rus,et al.  Design, fabrication and control of soft robots , 2015, Nature.

[16]  Robert J. Wood,et al.  A Vacuum-driven Origami “Magic-ball” Soft Gripper , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[17]  S. Levine Derivation of the ideal gas law , 1985 .

[18]  Stephen A. Morin,et al.  Soft Robotics: Review of Fluid‐Driven Intrinsically Soft Devices; Manufacturing, Sensing, Control, and Applications in Human‐Robot Interaction   , 2017 .

[19]  Fumiya Iida,et al.  Localized differential sensing of soft deformable surfaces , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[20]  Jianjun Yu,et al.  A Pneumatic Tactile Sensor for Co-Operative Robots , 2017, Sensors.

[21]  P. Rousseeuw Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .