A 3D-Printed Omni-Purpose Soft Gripper

Numerous soft grippers have been developed based on smart materials, pneumatic soft actuators, and underactuated compliant structures. In this article, we present a three-dimensional (3-D) printed omni-purpose soft gripper (OPSOG) that can grasp a wide variety of objects with different weights, sizes, shapes, textures, and stiffnesses. The soft gripper has a unique design that incorporates soft fingers and a suction cup that operate either separately or simultaneously to grasp specific objects. A bundle of 3-D-printable linear soft vacuum actuators (LSOVA) that generate a linear stroke upon activation is employed to drive the tendon-driven soft fingers. The support, fingers, suction cup, and actuation unit of the gripper were printed using a low-cost and open-source fused deposition modeling 3-D printer. A single LSOVA has a blocked force of 30.35 N, a rise time of 94 ms, a bandwidth of 2.81 Hz, and a lifetime of 26 120 cycles. The blocked force and stroke of the actuators are accurately predicted using finite element and analytical models. The OPSOG can grasp at least 20 different objects. The gripper has a maximum payload-to-weight ratio of 7.06, a grip force of 31.31 N, and a tip blocked force of 3.72 N

Automated Sensing Methods in Soft Stretchable Sensors for Soft Robotic Gripper

A soft robot is made from deformable and flexible materials such as silicone, rubber, polymers, etc. Soft robotics is a rapidly evolving field where the human-robot-interaction and bio-inspired design align. The physical characteristics such as highly deformable material and dexterity make soft robots widely applicable. A soft robotic gripper is a robotic hand that acts like a human hand and grasps any object. The most common applications of soft robotics grippers are gripping and locomotion in sensitive applications where high dynamic and sensitivity are essential. Nowadays, soft robotics grippers are used without any sensing method and feedback as it is crucial to make the output feedback from the gripper. The major drawback of soft robotic grippers is their need for more precision sensing. In traditional robots, we can integrate any sensor to detect the force and orientation of objects. Still, soft robotic grippers rely on the deformation sensing method, where the sensor must be highly flexible and deformable. With a precise sensing method, it is easier to determine the exact position or orientation of the object being gripped, and it limits the application of the soft robotic gripper. Sometimes, soft robots are employed in harsh environments to solve problems. With the sensing feedback, automation may become more reliable and succeed altogether. So, in this research, we have designed and fabricated a soft sensor to integrate with the gripper and to observe the feedback of the gripper. We propose integrated multimodal sensing that incorporates applied pressure and resistance change. The sensor provides feedback when the grippers hold any object, and the output response is the resistance change of the sensor. The liquid metal is susceptible and can respond to low force levels. We presented the 3D design, FEM simulation, fabrication, and integration of the gripper and sensor, and by showing both simulation and experimental results, the gripper is validated for real-time application. FEM simulation simulates behavior, optimizing design and predicting performance. We have designed and fabricated a soft sensor that yields microfluidic channel arrays embedded with liquid metal Galinstan alloy and a soft robotic gripper hand. Different printing processes and characterization results are presented for the sensor and actuator. The fabrication process of the gripper and sensor is adequately described. The gripper output characteristics are tested for bending angle, load test, elongation, and object holding under various applied pressure. Additionally, the sensor was tested for stretchability, linearity and durability, and human gesture integration with the finger, and this sensor can be easily reused/ reproduced. Furthermore, the sensor exhibits good sensitivity concerning different pressure and grasping various objects. Finally, we collected data using this sensor-integrated gripper and trained the dataset using machine learning models for automation. With more data, this can be an autonomous gripper with intelligent sensing methodologies. Moreover, this proposed stretchable sensor can be integrated into any existing gripper for innovative real-time applications

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

Advancing the Underactuated Grasping Capabilities of Single Actuator Prosthetic Hands

The last decade has seen significant advancements in upper limb prosthetics, specifically in the myoelectric control and powered prosthetic hand fields, leading to more active and social lifestyles for the upper limb amputee community. Notwithstanding the improvements in complexity and control of myoelectric prosthetic hands, grasping still remains one of the greatest challenges in robotics. Upper-limb amputees continue to prefer more antiquated body-powered or powered hook terminal devices that are favored for their control simplicity, lightweight and low cost; however, these devices are nominally unsightly and lack in grasp variety. The varying drawbacks of both complex myoelectric and simple body-powered devices have led to low adoption rates for all upper limb prostheses by amputees, which includes 35% pediatric and 23% adult rejection for complex devices and 45% pediatric and 26% adult rejection for body-powered devices [1]. My research focuses on progressing the grasping capabilities of prosthetic hands driven by simple control and a single motor, to combine the dexterous functionality of the more complex hands with the intuitive control of the more simplistic body-powered devices with the goal of helping upper limb amputees return to more active and social lifestyles. Optimization of a prosthetic hand driven by a single actuator requires the optimization of many facets of the hand. This includes optimization of the finger kinematics, underactuated mechanisms, geometry, materials and performance when completing activities of daily living. In my dissertation, I will present chapters dedicated to improving these subsystems of single actuator prosthetic hands to better replicate human hand function from simple control. First, I will present a framework created to optimize precision grasping – which is nominally unstable in underactuated configurations – from a single actuator. I will then present several novel mechanisms that allow a single actuator to map to higher degree of freedom motion and multiple commonly used grasp types. I will then discuss how fingerpad geometry and materials can better grasp acquisition and frictional properties within the hand while also providing a method of fabricating lightweight custom prostheses. Last, I will analyze the results of several human subject testing studies to evaluate the optimized hands performance on activities of daily living and compared to other commercially available prosthesis