Origami inspired design for capsule endoscope to retrograde using intestinal peristalsis

Capsule endoscopy has gained a lot of attention in the medical field in the recent past as an effective way of investigating unusual symptoms experienced in places such as esophagus, stomach, small intestine and colon. However, motion control of the capsule endoscope is challenging and often requires a power source and miniature actuators. To address these issues, we present a novel origami inspired structure as an attachment to the capsule endoscope. The proposed origami structure utilizes the wave generated by peristalsis of the intestine to move it forward and backward. When the origami structure is folded, the capsule endoscope is propelled forward by intestinal peristalsis. When the origami structure is unfolded, the intestinal peristalsis squeezes the origami structure to drive the capsule endoscope to move in the opposite direction. Therefore, folding and unfolding of the proposed origami structure would allow to control the movement direction of the capsule endoscope. In this paper, we present the design, simulations and experimental validation of the proposed origami structure

Design and Analysis of Exaggerated Rectilinear Gait-Based Snake-Inspired Robots

Snake-inspired locomotion is much more maneuverable compared to conventional locomotion concepts and it enables a robot to navigate through rough terrain. A rectilinear gait is quite flexible and has the following benefits: functionality on a wide variety of terrains, enables a highly stable robot platform, and provides pure undulatory motion without passive wheels. These benefits make rectilinear gaits especially suitable for search and rescue applications. However, previous robot designs utilizing rectilinear gaits were slow in speed and required considerable vertical motion. This dissertation will explore the development and implementation of a new exaggerated rectilinear gait that which will enable high speed locomotion and more efficient operation in a snake-inspired robot platform. The exaggerated rectilinear gait will emulate the natural snake's rectilinear gait to gain the benefit a snake's terrain adaptability, but the sequence and range of joint motion will be greatly exaggerated to achieve higher velocities to support robot speeds within the range of human walking speed. The following issues will be investigated in this dissertation. First, this dissertation will address the challenge of developing a snake-inspired robot capable of executing exaggerated rectilinear gaits. To successfully execute the exaggerated rectilinear gait, a snake-inspired robot platform must be able to perform high speed linear expansion/contraction and pivoting motions between segments. In addition to high speed joint motion, the new mechanical architecture much also incorporate a method for providing positive traction during gait execution. Second, a new exaggerated gait dynamics model will be developed using well established kinematics and dynamics analysis techniques. In addition to the exaggerated rectilinear gaits which emphasize high speed, a set of exaggerated rectilinear gaits which emphasize high traction will also be developed for application on difficult terrain types. Finally, an exaggerated rectilinear that emphasizes energy efficiency is defined and analyzed. This dissertation provides the foundations for realizing a high speed limbless locomotion capable of meeting the needs of the search, rescue, and recovery applications

A Review of SMA-Based Actuators for Bidirectional Rotational Motion: Application to Origami Robots

Shape memory alloys (SMAs) are a group of metallic alloys capable of sustaining large inelastic strains that can be recovered when subjected to a specific process between two distinct phases. Regarding their unique and outstanding properties, SMAs have drawn considerable attention in various domains and recently became appropriate candidates for origami robots, that require bi-directional rotational motion actuation with limited operational space. However, longitudinal motion-driven actuators are frequently investigated and commonly mentioned, whereas studies in SMA-based rotational motion actuation is still very limited in the literature. This work provides a review of different research efforts related to SMA-based actuators for bi-directional rotational motion (BRM), thus provides a survey and classification of current approaches and design tools that can be applied to origami robots in order to achieve shape-changing. For this purpose, analytical tools for description of actuator behaviour are presented, followed by characterisation and performance prediction. Afterward, the actuators’ design methods, sensing, and controlling strategies are discussed. Finally, open challenges are discussed

Robotic Actuation and Control with Programmable, Field-Activated Material Systems

This dissertation presents novel, field-activated smart material systems for the actuation and control of autonomous robots. Smart materials, a type of material whose properties can be changed with an external stimuli, represent a promising direction to expand upon existing robotic control and actuation methods, particularly in the sub-fields of soft robotics and robotic grasping. Specifically, this work makes the following contributions: i) a literature review that synthesizes recent work on field-activated smart materials and their use in soft robotics; ii) an electrorheological fluid (ERF) valve to control soft actuators; iii) magnetic elastomers (MEs) to increase the grip strength of soft grippers; and iv) a low-power method for torque transmission enabled by magnetorheological fluid (MRF) and electropermanent magnet arrays. After the introduction, this dissertation presents a comprehensive literature review paper (Chapter 2) regarding the use of field-activated materials in soft robotics, with an emphasis on magnetic elastomers. The second paper (Chapter 3) describes the development of a 3D-printed pressure valve intended to leverage the pressuring-holding properties of ERF when under the influence of a high voltage field to actuate soft actuators. The third paper (Chapter 4) demonstrates how magnetic elastomers and magnetic fields can enhance soft robotic grip strength and versatility. The fourth paper (Chapter 5) models, fabricates, and characterizes a MRF-containing clutch device able to rapidly and reversibly module the amount of torque transmitted from an input shaft to an output by leveraging low-power electropermanent magnet arrays. Each work focuses on a field-activated smart material to perform a specific robotic function, with particular emphasis given to compliant mechanisms and soft robotics, as well as to reducing cost and improving ease of fabrication with the use of modern fabrication techniques. In these described papers, field-activated materials are first modeled and then deployed in functional prototypes, and their robotic utility is described in detail after extensive experimental characterization

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

Models for reinforcement learning and design of a soft robot inspired by Drosophila larvae

Designs for robots are often inspired by animals, as they are designed mimicking animals’ mechanics, motions, behaviours and learning. The Drosophila, known as the fruit fly, is a well-studied model animal. In this thesis, the Drosophila larva is studied and the results are applied to robots. More specifically: a part of the Drosophila larva’s neural circuit for operant learning is modelled, based on which a synaptic plasticity model and a neural circuit model for operant learning, as well as a dynamic neural network for robot reinforcement learning, are developed; then Drosophila larva’s motor system for locomotion is studied, and based on it a soft robot system is designed. Operant learning is a concept similar to reinforcement learning in computer science, i.e. learning by reward or punishment for behaviour. Experiments have shown that a wide range of animals is capable of operant learning, including animal with only a few neurons, such as Drosophila. The fact implies that operant learning can establish without a large number of neurons. With it as an assumption, the structure and dynamics of synapses are investigated, and a synaptic plasticity model is proposed. The model includes nonlinear dynamics of synapses, especially receptor trafficking which affects synaptic strength. Tests of this model show it can enable operant learning at the neuron level and apply to a broad range of NNs, including feedforward, recurrent and spiking NNs. The mushroom body is a learning centre of the insect brain known and modelled for associative learning, but not yet for operant learning. To investigate whether it participates in operant learning, Drosophila larvae are studied with a transgenic tool by my collaborators. Based on the experiment and the results, a mushroom body model capable of operant learning is modelled. The proposed neural circuit model can reproduce the operant learning of the turning behaviour of Drosophila larvae. Then the synaptic plasticity model is simplified for robot learning. With the simplified model, a recurrent neural network with internal neural dynamics can learn to control a planar bipedal robot in a benchmark reinforcement learning task which is called bipedal walker by OpenAI. Benefiting efficiency in parameter space exploration instead of action space exploration, it is the first known solution to the task with reinforcement learning approaches. Although existing pneumatic soft robots can have multiple muscles embedded in a component, it is far less than the muscles in the Drosophila larva, which are well-organised in a tiny space. A soft robot system is developed based on the muscle pattern of the Drosophila larva, to explore the possibility to embed a high density of muscles in a limited space. Three versions of the body wall with pneumatic muscles mimicking the muscle pattern are designed. A pneumatic control system and embedded control system are also developed for controlling the robot. With a bioinspired body wall will a large number of muscles, the robot performs lifelike motions in experiments

Functional Soft Robotic Actuators Based on Dielectric Elastomers

Dielectric elastomer actuators (DEAs) are a promising soft actuator technology for robotics. Adding robotic functionalities--folding, variable stiffness, and adhesion--into their actuator design is a novel method to create functionalized robots with simplified actuator configurations. We first propose a foldable actuator that has a simple antagonistic DEA configuration allowing bidirectional actuation and passive folding. To prove the concept, a foldable elevon actuator with outline size of 70 mm × 130 mm is developed with a performance specification matched to a 400 mm wingspan micro air vehicle (MAV) of mass 130 g. The developed actuator exhibits actuation angles up to ± 26 ° and a torque of 2720 mN·mm in good agreement with a prediction model. During a flight, two of these integrated elevon actuators well controlled the MAV, as proven by a strong correlation of 0.7 between the control signal and the MAV motion. We next propose a variable stiffness actuator consisting of a pre-stretched DEA bonded on a low-melting-point alloy (LMPA) embedded silicone substrate. The phase of the LMPA changes between liquid and solid enabling variable stiffness of the structure, between soft and rigid states, while the DEA generates a bending actuation. A proof-of-concept actuator with dimension 40 mm length × 10mm width × 1mm thickness and a mass of 1 g is fabricated and characterized. Actuation is observed up to 47.5 ° angle and yielding up to 2.4 mN of force in the soft state. The stiffness in the rigid state is ~90 × larger than an actuator without LMPA. We develop a two-finger gripper in which the actuators act as the fingers. The rigid state allows picking up an object mass of 11 g (108 mN), to be picked up even though the actuated grasping force is only 2.4 mN. We finally propose an electroadhesion actuator that has a DEA design simultaneously maximizing electroadhesion and electrostatic actuation, while allowing self-sensing by employing an interdigitated electrode geometry. The concept is validated through development of a two-finger soft gripper, and experimental samples are characterized to address an optimal design. We observe that the proposed DEA design generates 10 × larger electroadhesion force compared to a conventional DEA design, equating to a gripper with a high holding force (3.5 N shear force for 1 cm^2) yet a low grasping force (1 mN). These features make the developed simple gripper to handle a wide range of challenging objects such as highly-deformable water balloons (35.6 g), flat paper (0.8 g), and a raw chicken egg (60.9 g), with its lightweight (1.5 g) and fast movement (100 ms to close fingers). The results in this thesis address the creation of the functionalized robots and expanding the use of DEAs in robotics