Using Redundant and Disjoint Time-Variant Soft Robotic Sensors for Accurate Static State Estimation

Soft robotic sensors have been limited in their applications due to their highly nonlinear time variant behavior. Current studies are either looking into techniques to improve the mechano-electrical properties of these sensors or into modelling algorithms that account for the history of each sensor. Here, we present a method for combining multi-material soft strain sensors to obtain equivalent higher quality sensors; better than each of the individual strain sensors. The core idea behind this work is to use a combination of redundant and disjoint strain sensors to compensate for the time-variant hidden states of a soft-bodied system, to finally obtain the true strain state in a static manner using a learning-based approach. We provide methods to develop these variable sensors and metrics to estimate their dissimilarity and efficacy of each sensor combinations, which can double down as a benchmarking tool for soft robotic sensors. The proposed approach is experimentally validated on a pneumatic actuator with embedded soft strain sensors. Our results show that static data from a combination of nonlinear time variant strain sensors is sufficient to accurately estimate the strain state of a system.Future and Emerging Technologies (FET) programme of the European Commission (grant agreement ID 828818

3D Printable Sensorized Soft Gelatin Hydrogel for Multi-Material Soft Structures

The ability to 3D print soft materials with integrated strain sensors enables significant flexibility for the design and fabrication of soft robots. Hydrogels provide an interesting alternative to traditional soft robot materials, allowing for more varied fabrication techniques. In this work, we investigate the 3D printing of a gelatin-glycerol hydrogel, where transglutaminase is used to catalyse the crosslinking of the hydrogel such that its material properties can be controlled for 3D printing. By including electron-conductive elements (aqueous carbon black) in the hydrogel we can create highly flexible and linear soft strain sensors. We present a first investigation into adapting a desktop 3D printer and optimizing its control parameters to fabricate sensorized 2D and 3D structures which can undergo >300% strain and show a response to strain which is highly linear and synchronous. To demonstrate the capabilities of this material and fabrication approach, we produce some example 2D and 3D structures and show their sensing capabilities

Design, fabrication and control of soft robots

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.National Science Foundation (U.S.) (Grant IIS-1226883

Review of machine learning methods in soft robotics

Soft robots have been extensively researched due to their flexible, deformable, and adaptive characteristics. However, compared to rigid robots, soft robots have issues in modeling, calibration, and control in that the innate characteristics of the soft materials can cause complex behaviors due to non-linearity and hysteresis. To overcome these limitations, recent studies have applied various approaches based on machine learning. This paper presents existing machine learning techniques in the soft robotic fields and categorizes the implementation of machine learning approaches in different soft robotic applications, which include soft sensors, soft actuators, and applications such as soft wearable robots. An analysis of the trends of different machine learning approaches with respect to different types of soft robot applications is presented; in addition to the current limitations in the research field, followed by a summary of the existing machine learning methods for soft robots

Soft pneumatic actuators with integrated resistive sensors enabled by multi-material 3D printing

The concept of soft robots has garnered significant attention in recent studies due to their unique capability to interact effectively with the surrounding environment. However, as the number of innovative soft pneumatic actuators (SPAs) continues to rise, integrating traditional sensors becomes challenging due to the complex and unrestricted movements exhibited by SPA during their operation. This article explores the importance of utilising one-shot multi-material 3D printing to integrate soft force and bending sensors into SPAs. It highlights the necessity of a well-tuned and robust low-cost fabrication process to ensure the functionality of these sensors over an extended period. Fused deposition modelling (FDM) offers a cost-effective solution for embedding sensors in soft robots, directly addressing such necessity. Also, a finite element method (FEM) based on the nonlinear hyper-elastic constitutive model equipped with experimental input is developed to precisely predict the deformation and tip force of the actuators measured in experiments. The dynamic mechanical test is conducted to observe and analyse the behaviour and resistance changes of conductive thermoplastic polyurethane (CTPU) and varioShore TPU (VTPU) during a cyclic test. The flexible sensor can detect deformations in SPAs through the application of air pressure. Similarly, the force sensor exhibits the ability to detect grasping objects by detecting changes in resistance. These findings suggest that the resistance change corresponds directly to the magnitude of the mechanical stimuli applied. Thus, the device shows potential for functioning as a resistive sensor for soft actuation. Furthermore, these findings highlight the significant potential of 3D and 4D printing technology in one-shot fabrication of soft sensor-actuator robotic systems, suggesting promising applications in various fields like grippers with sensors and rehabilitation devices

Sensing and actuation for the design of upper limb prosthetics

The objective of this thesis has been to improve upper limb prosthetics. With this aim in mind, and based on reported user needs, we targeted two main aspects of contemporary active prosthetics: sensing and actuation. The restoration of proprioceptive capabilities through the artificial limb is vital for their intuitive and precise control. In order to capture the prosthetics position, we designed extremely soft microfluidic sensors using conductive liquids such as eutectic Gallium Indium (eGaIn) or Room Temperature Ionic Liquid (RTIL) embedded in soft elastomers. These sensors were used first to sense unidirectional strain, then normal force through Electrical Impedance Tomography (EIT) in a soft microfluidic skin, and were finally embedded in a soft artificial skin that was used to measure the human hand motion. Conventional electromagnetic actuators are poorly suited for prosthetic actuation. Grasping tasks typically require large torque at low speeds whereas conventional actuators are designed to be efficient at high rotational speeds. In consequence, we designed the "Programmable Permanent Magnet" (PPM) actuator. This unique actuator, based on the magnetization of permanent magnets by current pulses, is able to maintain a large torque at no speed and for no energetic cost. This actuator is especially suited for tasks such as grasping or walking and represents a new type of electromagnetic actuator that will enable efficient low speed high torque efficient actuation for robotic and prosthetic applications

Soft pneumatic actuators: a review of design, fabrication, modeling, sensing, control and applications

Soft robotics is a rapidly evolving field where robots are fabricated using highly deformable materials and usually follow a bioinspired design. Their high dexterity and safety make them ideal for applications such as gripping, locomotion, and biomedical devices, where the environment is highly dynamic and sensitive to physical interaction. Pneumatic actuation remains the dominant technology in soft robotics due to its low cost and mass, fast response time, and easy implementation. Given the significant number of publications in soft robotics over recent years, newcomers and even established researchers may have difficulty assessing the state of the art. To address this issue, this article summarizes the development of soft pneumatic actuators and robots up until the date of publication. The scope of this article includes the design, modeling, fabrication, actuation, characterization, sensing, control, and applications of soft robotic devices. In addition to a historical overview, there is a special emphasis on recent advances such as novel designs, differential simulators, analytical and numerical modeling methods, topology optimization, data-driven modeling and control methods, hardware control boards, and nonlinear estimation and control techniques. Finally, the capabilities and limitations of soft pneumatic actuators and robots are discussed and directions for future research are identified

DEVELOPMENT OF A NANOCOMPOSITE SENSOR AND ELECTRONIC SYSTEM FOR MONITORING OF LOCOMOTION OF A SOFT EARTHWORM ROBOT

The ability to detect external stimuli and perceive the surrounding areas represents a key feature of modern soft robotic systems, used for exploration of harsh environments. Although people have developed various types of biomimetic soft robots, no integratedsensor system is available to provide feedback locomotion. Here, a stretchable nanocomposite strain sensor with integrated wireless electronics to provide a feedbackloop locomotion of a soft robotic earthworm is presented. The ultrathin and soft strain sensor based on a carbon nanomaterial and a low-modulus silicone elastomer allows for a seamless integration with the body of the soft robot, accommodating large strains derived from bending, stretching, and physical interactions with obstacles. A scalable, costeffective, screen-printing method manufactures an array of strain sensors that are conductive and stretchable over 100% with a gauge factor over 38. An array of stretchable nanomembrane interconnectors enables a reliable connection between soft strain sensors and wireless electronics, while tolerating the robot’s multi-modal movements. A set of computational and experimental studies of soft materials, stretchable mechanics, and hybrid packaging provides key design factors for a reliable, nanocomposite sensor system. The miniaturized wireless circuit, embedded in the robot joint, offers a real-time monitoring of strain changes on the earthworm skin. Collectively, the soft sensor system shows a great potential to be integrated with other flexible, stretchable electronics for applications in soft robotics, wearable devices, and human-machine interfaces.M.S

Sensors for Robotic Hands: A Survey of State of the Art

Recent decades have seen significant progress in the field of artificial hands. Most of the surveys, which try to capture the latest developments in this field, focused on actuation and control systems of these devices. In this paper, our goal is to provide a comprehensive survey of the sensors for artificial hands. In order to present the evolution of the field, we cover five year periods starting at the turn of the millennium. At each period, we present the robot hands with a focus on their sensor systems dividing them into categories, such as prosthetics, research devices, and industrial end-effectors.We also cover the sensors developed for robot hand usage in each era. Finally, the period between 2010 and 2015 introduces the reader to the state of the art and also hints to the future directions in the sensor development for artificial hands

Utilizing Compliance To Address Modern Challenges in Robotics

Mechanical compliance will be an essential component for agile robots as they begin to leave the laboratory settings and join our world. The most crucial finding of this dissertation is showing how lessons learned from soft robotics can be adapted into traditional robotics to introduce compliance. Therefore, it presents practical knowledge on how to build soft bodied sensor and actuation modules: first example being soft-bodied curvature sensors. These sensors contain both standard electronic components soldered on flexible PCBs and hyperelastic materials that cover the electronics. They are built by curing multi-material composites inside hyper elastic materials. Then it shows, via precise sensing by using magnets and Hall-effect sensors, how closed-loop control of soft actuation modules can be achieved via proprioceptive feedback. Once curvature sensing idea is verified, the dissertation describes how the same sensing methodology, along with the same multi-material manufacturing technique can be utilized to construct soft bodied tri-axial force sensors. It shows experimentally that these sensors can be used by traditional robotic grippers to increase grasping quality. At this point, I observe that compliance is an important property that robots may utilize for different types of motions. One example being Raibert\u27s 2D hopper mechanism. It uses its leg-spring to store energy while on the ground and release this energy before jumping. I observe that via soft material design, it would be possible to embed compliance directly into the linkage design itself. So I go over the design details of an extremely lightweight compliant five-bar mechanism design that can store energy when compressed via soft ligaments embedded in its joints. I experimentally show that the compliant leg design offers increased efficiency compared to a rigid counterpart. I also utilize the previously mentioned soft bodied force sensors for rapid contact detection (~5-10 Hz) in the hopper test platform. In the end, this thesis connects soft robotics with the traditional body of robotic knowledge in two aspects: a) I show that manufacturing techniques we use for soft bodied sensor/actuator designs can be utilized for creating soft ligaments that add strength and compliance to robot joints; and b) I demonstrate that soft bodied force sensing techniques can be used reliably for robotic contact detection