Design and Fabrication of Soft 3D Printed Actuators: Expanding Soft Robotics Applications

Soft pneumatic actuators are ideal for soft robotic applications due to their innate compliance and high power-weight ratios. Presently, the majority of soft pneumatic actuators are used to create bending motions, with very few able to produce significant linear movements. Fewer can actively produce strains in multiple directions. The further development of these actuators is limited by their fabrication methods, specifically the lack of suitable stretchable materials for 3D printing. In this thesis, a new highly elastic resin for digital light projection 3D printers, designated ElastAMBER, is developed and evaluated, which shows improvements over previously synthesised elastic resins. It is prepared from a di-functional polyether urethane acrylate oligomer and a blend of two different diluent monomers. ElastAMBER exhibits a viscosity of 1000 mPa.s at 40 °C, allowing easy printing at near room temperatures. The 3D-printed components present an elastomeric behaviour with a maximum extension ratio of 4.02 ± 0.06, an ultimate tensile strength of (1.23 ± 0.09) MPa, low hysteresis, and negligible viscoelastic relaxation

Human Motor Control and the Design and Control of Backdriveable Actuators for Human-Robot Interaction

The design of the control and hardware systems for a robot intended for interaction with a human user can profit from a critical analysis of the human neuromotor system and human biomechanics. The primary observation to be made about the human control and ``hardware’’ systems is that they work well together, perhaps because they were designed for each other. Despite the limited force production and elasticity of muscle, and despite slow information transmission, the sensorimotor system is adept at an impressive range of motor behaviors. In this thesis I present three explorations on the manners in which the human and hardware systems work together, hoping to inform the design of robots suitable for human-robot interaction. First, I used the serial reaction time (SRT) task with cuing from lights and motorized keys to assess the relative contribution of visual and haptic stimuli to the formation of motor and perceptual memories. Motorized keys were used to deliver brief pulse-like displacements to the resting fingers, with the expectation that the proximity and similarity of these cues to the response motor actions (finger-activated key-presses) would strengthen the motor memory trace in particular. Error rate results demonstrate that haptic cues promote motor learning over perceptual learning. The second exploration involves the design of an actuator specialized for human-robot interaction. Like muscle, it features series elasticity and thus displays good backdrivability. The elasticity arises from the use of a compressible fluid while hinged rigid plates are used to convert fluid power into mechanical power. I also propose impedance control with dynamics compensation to further reduce the driving-point impedance. The controller is robust to all kinds of uncertainties. The third exploration involves human control in interaction with the environment. I propose a framework that accommodates delays and does not require an explicit model of the musculoskeletal system and environment. Instead, loads from the biomechanics and coupled environment are estimated using the relationship between the motor command and its responses. Delays inherent in sensory feedback are accommodated by taking the form of the Smith predictor. Agreements between simulation results and empirical movements suggests that the framework is viable.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120675/1/gloryn_1.pd

First-Order Dynamic Modeling and Control of Soft Robots

Modeling of soft robots is typically performed at the static level or at a second-order fully dynamic level. Controllers developed upon these models have several advantages and disadvantages. Static controllers, based on the kinematic relations tend to be the easiest to develop, but by sacrificing accuracy, efficiency and the natural dynamics. Controllers developed using second-order dynamic models tend to be computationally expensive, but allow optimal control. Here we propose that the dynamic model of a soft robot can be reduced to first-order dynamical equation owing to their high damping and low inertial properties, as typically observed in nature, with minimal loss in accuracy. This paper investigates the validity of this assumption and the advantages it provides to the modeling and control of soft robots. Our results demonstrate that this model approximation is a powerful tool for developing closed-loop task-space dynamic controllers for soft robots by simplifying the planning and sensory feedback process with minimal effects on the controller accuracy

Stochastic Approach for Modeling a Soft Robotic Finger with Creep Behavior

Soft robots have high adaptability and safeness which are derived from their softness, and therefore it is paid attention to use them in human society. However, the controllability of soft robots is not enough to perform dexterous behaviors when considering soft robots as alternative laborers for humans. The model-based control is effective to achieve dexterous behaviors. When considering building a model which is suitable for control, there are problems based on their special properties such as the creep behavior or the variability of motion. In this paper, the lumped parameterized model with viscoelastic joints for a soft finger is established for the creep behavior. Parameters are expressed as distributions, which makes it possible to take into account the variability of motion. Furthermore, stochastic analyses are performed based on the parameters' distribution. They show high adaptivity compared with experimental results and also enable the investigation of the effects of parameters for robots' variability.Comment: 17 pages, 8 figures. This is a preprint of an article submitted for consideration in Advanced Robotics, copyright Taylor & Francis and Robotics Society of Japan; Advanced Robotics is available online at http://www.tandfonline.com

Design and Analysis of Soft Actuator with Enhanced Stiffness with Granular Jamming

The field of soft robotics has been increasing popularity and importance in last decade with its groundbreaking applications in the field of delicate food handling industry and rehabilitation of limbs and fingers of stroke affected patients. The area of soft robotics seeks to improve robot safety, allowing them to function in circumstances where standard robots cannot. This research is focused on pneumatically actuated soft robots as they are efficient, easily controlled, affordable, and well researched. These robots consist of one or more soft actuators, made of silicone elastomers with low material hardness. Low hardness silicone actuators are structurally weak and cannot generate functional forces, which can be rectified by simply increasing the hardness of the material, resulting in compromising softness of the robot. This research attempts to provide a solution to increase structural stability and force output of soft actuator without compromising softness of the material. These were achieved in two ways; one, by improving the cross-sectional profile of the actuator, with an addition of vacuum functionality which increases degree of freedom by one. Two, by attaching a granular jamming component to the actuator, which can change its stiffness actively based on the vacuum applied to it. In this research, the soft actuator was made of Eco-Flex 00-30 silicone and ground coffee was used as granular material for jamming. The actuator was designed on CATIA, and simulation analysis was carried out in ANSYS. A simulation study is conducted to optimize the design parameters to improve bending angle. The jamming components are attached on either side of the actuator and filled with ground coffee which provides controlled stiffness. The actuator was fabricated by molding, all molds are 3D printed with polylactic acid. The actuator was powered by an electric air pump. The actuator is evaluated for bending angle and blocking force at the tip. 280% more bending was achieved under vacuum when compared to conventional design. The blocking force was increased by 270% upon implementing jamming component. The force output obtained per unit pressure applied when compared to present literature increased by 4 times. Lastly, these methods can be implemented to improve the performance of any soft pneumatic actuators