Safe Grasping with a Force Controlled Soft Robotic Hand

Safe yet stable grasping requires a robotic hand to apply sufficient force on the object to immobilize it while keeping it from getting damaged. Soft robotic hands have been proposed for safe grasping due to their passive compliance, but even such a hand can crush objects if the applied force is too high. Thus for safe grasping, regulating the grasping force is of uttermost importance even with soft hands. In this work, we present a force controlled soft hand and use it to achieve safe grasping. To this end, resistive force and bend sensors are integrated in a soft hand, and a data-driven calibration method is proposed to estimate contact interaction forces. Given the force readings, the pneumatic pressures are regulated using a proportional-integral controller to achieve desired force. The controller is experimentally evaluated and benchmarked by grasping easily deformable objects such as plastic and paper cups without neither dropping nor deforming them. Together, the results demonstrate that our force controlled soft hand can grasp deformable objects in a safe yet stable manner.Comment: Accepted to 2020 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2020

3D printed pneumatic soft actuators and sensors: their modeling, performance quantification, control and applications in soft robotic systems

Continued technological progress in robotic systems has led to more applications where robots and humans operate in close proximity and even physical contact in some cases. Soft robots, which are primarily made of highly compliant and deformable materials, provide inherently safe features, unlike conventional robots that are made of stiff and rigid components. These robots are ideal for interacting safely with humans and operating in highly dynamic environments. Soft robotics is a rapidly developing field exploiting biomimetic design principles, novel sensor and actuation concepts, and advanced manufacturing techniques. This work presents novel soft pneumatic actuators and sensors that are directly 3D printed in one manufacturing step without requiring postprocessing and support materials using low-cost and open-source fused deposition modeling (FDM) 3D printers that employ an off-the-shelf commercially available soft thermoplastic poly(urethane) (TPU). The performance of the soft actuators and sensors developed is optimized and predicted using finite element modeling (FEM) analytical models in some cases. A hyperelastic material model is developed for the TPU based on its experimental stress-strain data for use in FEM analysis. The novel soft vacuum bending (SOVA) and linear (LSOVA) actuators reported can be used in diverse robotic applications including locomotion robots, adaptive grippers, parallel manipulators, artificial muscles, modular robots, prosthetic hands, and prosthetic fingers. Also, the novel soft pneumatic sensing chambers (SPSC) developed can be used in diverse interactive human-machine interfaces including wearable gloves for virtual reality applications and controllers for soft adaptive grippers, soft push buttons for science, technology, engineering, and mathematics (STEM) education platforms, haptic feedback devices for rehabilitation, game controllers and throttle controllers for gaming and bending sensors for soft prosthetic hands. These SPSCs are directly 3D printed and embedded in a monolithic soft robotic finger as position and touch sensors for real-time position and force control. One of the aims of soft robotics is to design and fabricate robotic systems with a monolithic topology embedded with its actuators and sensors such that they can safely interact with their immediate physical environment. The results and conclusions of this thesis have significantly contributed to the realization of this aim

Scalability study for robotic hand platform

The goal of this thesis project was to determine the lower limit of scale for the RIT robotic grasping hand. This was accomplished using a combination of computer simulation and experimental studies. A force analysis was conducted to determine the size of air muscles required to achieve appropriate contact forces at a smaller scale. Input variables, such as the actuation force and tendon return force, were determined experimentally. A dynamic computer model of the hand system was then created using Recurdyn. This was used to predict the contact (grasping) force of the fingers at full-scale, half-scale, and quarter-scale. Correlation between the computer model and physical testing was achieved for both a life-size and half-scale finger assembly. To further demonstrate the scalability of the hand design, both half and quarter-scale robotic hand rapid prototype assemblies were built using 3D printing techniques. This thesis work identified the point where further miniaturization would require a change in the manufacturing process to micro-fabrication. Several techniques were compared as potential methods for making a production intent quarter-scale robotic hand. Investment casting, Swiss machining, and Selective Laser Sintering were the manufacturing techniques considered. A quarter-scale robotic hand tested the limits of each technology. Below this scale, micro-machining would be required. The break point for the current actuation method, air muscles, was also explored. Below the quarter-scale, an alternative actuation method would also be required. Electroactive Polymers were discussed as an option for the micro-scale. In summary, a dynamic model of the RIT robotic grasping hand was created and validated as scalable at full and half-scales. The model was then used to predict finger contact forces at the quarter-scale. The quarter-scale was identified as the break point in terms of the current RIT robotic grasping hand based on both manufacturing and actuation. A novel, prototype quarter-scale robotic hand assembly was successfully built by an additive manufacturing process, a high resolution 3D printer. However, further miniaturization would require alternate manufacturing techniques and actuation mechanisms

Scalable Tactile Sensing for an Omni-adaptive Soft Robot Finger

Robotic fingers made of soft material and compliant structures usually lead to superior adaptation when interacting with the unstructured physical environment. In this paper, we present an embedded sensing solution using optical fibers for an omni-adaptive soft robotic finger with exceptional adaptation in all directions. In particular, we managed to insert a pair of optical fibers inside the finger's structural cavity without interfering with its adaptive performance. The resultant integration is scalable as a versatile, low-cost, and moisture-proof solution for physically safe human-robot interaction. In addition, we experimented with our finger design for an object sorting task and identified sectional diameters of 94\% objects within the $\pm$6mm error and measured 80\% of the structural strains within $\pm$0.1mm/mm error. The proposed sensor design opens many doors in future applications of soft robotics for scalable and adaptive physical interactions in the unstructured environment.Comment: 8 pages, 6 figures, full-length version of a submission to IEEE RoboSoft 202

A Novel Fiber Jamming Theory and Experimental Verification

This thesis developed a novel theory of fiber jamming and experimentally verified it. The theory relates the performance, which is the ratio between the stiff and soft states of a fiber jamming chamber, to three relative design parameters: the ratio of the wall thickness to the membrane inner diameter, the ratio of the fiber diameter to membrane inner diameter, and the number of fibers. These three parameters, when held constant across different chamber sizes, hold the performance constant. To test the theory, three different types of fiber jamming chambers were built in three different sizes. Each chamber was set up as a cantilever beam and deflected 10mm in both the un-jammed (soft) and jammed (stiff) states. When the three design parameters were held constant, the performance of the chamber was consistent within 10\%. In contrast, when the parameters were altered, there was a statistically significant $p \u3c .0001$ and noticeable effect on chamber performance. These two results can be used in tandem to design miniaturized fiber jamming chambers. These results also have a direct application in soft robots designed for minimally invasive surgery

Tactile object class and internal state recognition for mobile manipulation

Abstract — Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. In this work, we present a tactile perception strategy that allows any mobile robot with tactile sensors in its gripper to measure a set of generic tactile features while grasping an object. We propose a hybrid velocity-force controller, that grasps an object safely and reveals at the same time its deformation properties. As an application, we show that a robot can use these features to distinguish the open/closed and fill state of bottles and cans – purely from tactile sensing – from a small training set. To prove that this is a hard recognition problem, we also conducted a comperative study with 17 human test subjects. We found that the recognition rate of the human subjects were comparable to our robotic gripper. I