Mechanical engineering doctoral student Caroline Schell and postdoctoral associate Peter Bui take us inside the emerging field of soft robotics in this experTU video. Members of Biological Robotics at Tulsa, these scholars understand what it takes to make their soft robot, fittingly named “Squishy,” respond to its environment, fragile objects and touch.
In an earlier paper published in Frontiers in Robotics and AI, Schultz and Postdoctoral Associate Peter (Phuc D.H.) Bui reported on the development of a semilinear parameter-varying observer (state estimator) they tested on an inflatable, fabric-reinforced soft robot named Squishy. Drawing on that work, for their ICRA presentation the duo, along with collaborators at Brigham Young University, focused on a method for dynamically simulating soft robots to predict their future movements.
“The simulation environment presented at ICRA is really the flip side of the state estimator [described in the Frontiers article] coin,” remarked Schultz. “We shared with conference attendees our findings on how to simulate the movement of robots like ‘Squishy’ (TU’s inflatable fabric-reinforced tentacle robot), which allows us to predict where it will be in the future.”
Schultz and his colleagues expect that the new “disc-thread” simulation environment will better represent motions that occur within Squishy’s wrinkles, pleats and folds. By combining their earlier work with their more recent investigation, Schultz says they should be able to control the robot and drive it to a sequence of positions and shapes that will complete a useful task, such as cleaning or polishing a surface.
Meet Squishy and learn more about soft robotics and the related research going on at TU in this short video.
The research reported in this story is supported by NSF grant No. 1935312 EFRI C3 SoRo: Between a Soft Robot and a Hard Place: Estimation and Control Algorithms that Exploit Soft Robots’ Unique Abilities.
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