Multi-Segment Parallel Continuum Manipulator

Continuum manipulators are a type of robot arm that resemble biological tentacles and trunks. They have a flexible and compliant structure, which may allow them to out-perform rigid-link designs in cluttered workspaces or in environments that contain people. While most continuum manipulators are required to have constant curvature along the length of each segment, a new design known as a parallel continuum manipulator removes this restriction and inherits some properties of parallel rigid-link robots such as greater stability, precision, strength, and maneuverability. Until now, only single segment forms of these manipulators have been created. This project expands this manipulator design concept by creating the first multi-segment parallel continuum manipulator

Novel design of a soft lightweight pneumatic continuum robot arm with decoupled variable stiffness and positioning

Soft robot arms possess unique capabilities when it comes to adaptability, flexibility and dexterity. In addition, soft systems that are pneumatically actuated can claim high power to weight ratio. One of the main drawbacks of pneumatically actuated soft arms is that their stiffness cannot be varied independently from their end-effector position in space. The novel robot arm physical design presented in this paper successfully decouples its end-effector positioning from its stiffness. An experimental characterisation of this ability is coupled with a mathematical analysis. The arm combines the light weight, high payload to weight ratio and robustness of pneumatic actuation with the adaptability and versatility of variable stiffness. Light weight is a vital component of the inherent safety approach to physical human-robot interaction. In order to characterise the arm, a neural network analysis of the curvature of the arm for different input pressures is performed. The curvature-pressure relationship is also characterised experimentally

Surrogate models for the design and control of soft mechanical systems

Soft mechanical systems constitute stretchable skins, tissue-like appendages, fibers and fluids, and utilize material deformation to transmit forces or motion to perform a mechanical task. These systems may possess infinite degrees of freedom with finite modes of actuation and sensing, and this creates challenges in modeling, design and controls. This thesis explores the use of surrogate models to approximate the complex physics between the inputs and outputs of a soft mechanical system composed of a ubiquitous soft building block known as Fiber Reinforced Elastomeric Enclosures (FREEs). Towards this the thesis is divided into two parts, with the first part investigating reduced order models for design and the other part investigating reinforcement learning (RL) framework for controls. The reduced order models for design is motivated by the need for repeated quick and accurate evaluation of the system performance. Two mechanics-based models are investigated: (a) A Pseudo Rigid Body model (PRB) with lumped spring and link elements, and (b) a Homogenized Strain Induced (HIS) model that can be implemented in a finite element framework. The parameters of the two models are fit either directly with experiments on FREE prototypes or with a high fidelity robust finite element model. These models capture fundamental insights on design by isolating a fundamental dyad building block of contracting FREEs that can be configured to either obtain large stroke (displacement) or large force. Furthermore, the thesis proposes a novel building block-based design framework where soft FREE actuators are systematically integrated in a compliant system to yield a given motion requirement. The design process is deemed useful in shape morphing adaptive structures such as airfoils, soft skins, and wearable devices for the upper extremities. Soft robotic systems such as manipulators are challenging to control because of their flexibility, ability to undergo large spatial deformations that are dependent on the external load. The second part of this work focuses on the control of a unique soft continuum arm known as the BR2 manipulator using reinforcement learning (RL). The BR2 manipulator has a unique parallel architecture with a combined bending mode and torsional modes, and its inherent asymmetric nature precludes well defined analytical models to capture its forward kinematics. Two RL-based frameworks are evaluated on the BR2 manipulator and their efficacy in carrying out position control using simple state feedback is reported in this work. The results highlight external load invariance of the learnt control policies which is a significant factor for deformable continuum arms for applications involving pick and place operations. The manipulator is deemed useful in berry harvesting and other agricultural applications

Actuators and sensors for application in agricultural robots: A review

In recent years, with the rapid development of science and technology, agricultural robots have gradually begun to replace humans, to complete various agricultural operations, changing traditional agricultural production methods. Not only is the labor input reduced, but also the production efficiency can be improved, which invariably contributes to the development of smart agriculture. This paper reviews the core technologies used for agricultural robots in non-structural environments. In addition, we review the technological progress of drive systems, control strategies, end-effectors, robotic arms, environmental perception, and other related systems. This research shows that in a non-structured agricultural environment, using cameras and light detection and ranging (LiDAR), as well as ultrasonic and satellite navigation equipment, and by integrating sensing, transmission, control, and operation, different types of actuators can be innovatively designed and developed to drive the advance of agricultural robots, to meet the delicate and complex requirements of agricultural products as operational objects, such that better productivity and standardization of agriculture can be achieved. In summary, agricultural production is developing toward a data-driven, standardized, and unmanned approach, with smart agriculture supported by actuator-driven-based agricultural robots. This paper concludes with a summary of the main existing technologies and challenges in the development of actuators for applications in agricultural robots, and the outlook regarding the primary development directions of agricultural robots in the near future

SOFT ROBOTIC APPENDAGES USING PNEUMATIC ARTIFICIAL MUSCLES

This dissertation focuses on advancing the state of the art in soft robotics using pneumatic artificial (PAM) actuators. Pneumatic artificial muscles are currently used in robotic and prosthetic applications due to their high power to weight ratio, controllable compliance, and simple design. Contractile PAMs are typically used in traditional hard robotics in place of heavy electric motors. As the field of soft robotics grows, extensile PAMs are beginning to have increased usage. The bladder of a PAM affects common actuator performance metrics, specifically: blocked force, free contraction, hysteresis, and dead-band pressure. This work investigates the effect that bladder thickness has on static actuation performance of small scale PAMs. Miniature PAMs were fabricated with a range of bladder thicknesses then experimentally characterized in quasi-static conditions, where results showed that increasing bladder wall thickness decreases blocked force and free contraction, while the dead-band pressure increases. A nonlinear model was then applied to determine the structure of the stress-strain relationship that enables accurate modeling and the minimum number of terms. Contractile and extensile PAMs were experimentally fabricated and parametrically compared to demonstrate the advantages and disadvantages of each type of PAM and applications for which they are best suited. An additional PAM model was developed based on finite strain theory to address the lack of predicitive models. The closed-form pneumatic artificial muscle quasi-static actuator force is obtained. The analysis was experimentally validated using actuation force versus contraction ratio test data at a series of discrete inflation pressures for four different pneumatic artificial muscles, two contractile and two extensile. This work investigates adding bio-inspired ossicle structures from brittle stars to pneumatic artificial muscle continuum arm sections. The ossicle structure increases the range of motion and load capability of the continuum arm section while reducing the pneumatic pressure requirements. In this work, a static model of the continuum arm section is developed assuming constant curvature in the section and finding the center of mass of the section and its end plate. This model is validated by comparing the pressure-angle relationship at various loading conditions

Pneumatic variable stiffness soft robot end effectors

Traditionally, robots have been formed from heavy rigid materials and have used stiff actuator technologies. This means they are not well suited to operation near humans due to the associated high risk of injury, should a collision occur. Additionally, rigid robots are not well suited to operation in an unstructured environment where they may come into contact with obstacles. Furthermore, traditional stiff robots can struggle to grasp delicate objects as high localised forces can damage the item being held. The relatively new field of soft robotics is inspired by nature, particularly animals which do not have skeletons but which still have the ability to move and grasp in a skilful manner. Soft robotics seeks to replicate this ability through the use of new actuation technologies and materials. This research presents the design of a variable stiffness, soft, three-fingered dexterous gripper. The gripper uses contractor pneumatic muscles to control the motion of soft fingers. The soft nature of the gripper means it can deform if it collides with obstacles, and because grasping forces are spread over a larger area the chance of damaging the object being held is reduced. The gripper has the ability to vary its stiffness depending upon how it is to be used, and in this regard two methods of varying the stiffness are explored. In the first method, the finger is formed from an extensor muscle which acts antagonistically against the contractor muscles. Increasing the total pressure in the system increases the stiffness of the fingers. The second approach uses granular jamming to vary the stiffness of the actual finger structure. This thesis explores the behaviour of both extensor and contractor pneumatic muscles and develops a new simplified mathematical model of the actuator’s behaviour. The two methods of stiffness variation are then assessed experimentally. A number of multi-fingered grippers are then designed and their kinematics determined before prototypes are presented. Control of the grippers was then explored, along with the ability to adjust the stiffness of the grasp

Impact of Ear Occlusion on In-Ear Sounds Generated by Intra-oral Behaviors

We conducted a case study with one volunteer and a recording setup to detect sounds induced by the actions: jaw clenching, tooth grinding, reading, eating, and drinking. The setup consisted of two in-ear microphones, where the left ear was semi-occluded with a commercially available earpiece and the right ear was occluded with a mouldable silicon ear piece. Investigations in the time and frequency domains demonstrated that for behaviors such as eating, tooth grinding, and reading, sounds could be recorded with both sensors. For jaw clenching, however, occluding the ear with a mouldable piece was necessary to enable its detection. This can be attributed to the fact that the mouldable ear piece sealed the ear canal and isolated it from the environment, resulting in a detectable change in pressure. In conclusion, our work suggests that detecting behaviors such as eating, grinding, reading with a semi-occluded ear is possible, whereas, behaviors such as clenching require the complete occlusion of the ear if the activity should be easily detectable. Nevertheless, the latter approach may limit real-world applicability because it hinders the hearing capabilities.</p