Soft Robotic Fingers with Embedded Ionogel Sensors and Discrete Actuation Modes for Somatosensitive Manipulation
Soft robotic grippers enable gentle, adaptive, and bioinspired manipulation that is simply not possible using traditional rigid robots. However, it has remained challenging to create multi-degree-of-freedom soft actuators with appropriate sensory capabilities for soft manipulators requiring greater dexterity and closed-loop control. In this work, we use embedded 3D printing to produce soft robotic fingers with discrete actuation modes and integrated ionogel soft sensors that provide proprioceptive and tactile sensing corresponding to each degree of freedom. With new readout electronics that streamline the measurement of sensor resistance, we evaluate the fingers’ sensory feedback through free and blocked displacement experiments. We integrate three of our sensorized fingers together to create a soft manipulator with different grasping poses. Finally, we showcase the importance of the fingers’ discrete actuation modes and integrated sensors via a closed-loop grasping study. Our methods demonstrate an enabling manufacturing platform that can be adapted to create other soft multi-DOF manipulators requiring somatosensory feedback for a variety of closed-loop and machine learning-based control algorithms.
R. Truby, R. Katzschmann, J. Lewis, D. Rus, “Soft Robotic Fingers with Embedded Ionogel Sensors and Discrete Actuation Modes for Somatosensitive Manipulation.” IEEE RoboSoft, Apr 2019. [PDF]
Robust Proprioceptive Grasping with a Soft Robot Hand
We developed a soft hand that is capable of robustly grasping and identifying objects based on internal state measurements along with a system that autonomously performs grasps. The highly compliant soft hand allows for intrinsic robustness to grasping uncertainties. The addition of internal sensing allows the configuration of the hand and object to be detected. The finger module includes resistive force sensors on the fingertips for contact detection and resistive bend sensors for measuring the curvature profile of the finger. The curvature sensors can be used to estimate the contact geometry. This capability allows to distinguish between a set of grasped objects. With one data point from each finger, the object can be identified by grasping it. A clustering algorithm finds the correspondence for each grasped object. We tested this for both enveloping grasps and pinch grasps. A closed loop system uses a camera to detect approximate object locations. Compliance in the soft hand handles that uncertainty in addition to geometric uncertainty in the shape of the object.
B. Homberg*, R. Katzschmann*, M. Dogar, and D. Rus, “Haptic Identification of Objects using a Modular Soft Robotic Gripper,” IROS, Hamburg, Sept. 2015. [PDF]
B. Homberg*, R. Katzschmann*, M. Dogar, D. Rus, “Robust Proprioceptive Grasping with a Soft Robot Hand.” Autonomous Robots, Apr 2018. [PDF]
News Articles (Sept. 2015): “Soft robotic gripper can pick up and identify wide array of objects” featured in BBC, Scientific American, CNBC, VICE, Popular Science, Boston Globe, Bloomberg Radio, Washington Post, NBC News, Quartz, Christian Science Monitor, Gizmodo, Slashgear, BostInno, etc.
Printable Hydraulics for Soft Grippers
This work introduces a novel technique for fabricating functional robots using 3D printers. Simultaneously depositing photopolymers and a non-curing liquid allows complex, pre-filled fluidic channels to be fabricated. This new printing capability enables complex hydraulically actuated robots and robotic components to be automatically built, with no assembly required. The technique is showcased by printing linear bellows actuators, gear pumps, soft grippers and a hexapod robot, using a commercially-available 3D printer. We detail the steps required to modify the printer and describe the design constraints imposed by this new fabrication approach.
R. MacCurdy, R. Katzschmann, Y. Kim, and D. Rus, “Printable hydraulics: A method for fabricating robots by 3D co-printing solids and liquids.” ICRA, Stockholm, 2016. [PDF]
News Articles (July 2016): “First-ever 3-D printed robots made of both solids and liquids“ featured in
CBS News, Wired, BBC News, The Verge, Washington Post, Popular Science, ZDNet, Quartz, PC Mag, CNET, Digital Trends, Daily Mail, Engadget, Fast Company, Mashable, Boston Magazine, Vice, Gizmodo, ABC News, Gizmag, Yahoo Finance, etc.