Control Space Reduction and Real-Time Accurate Modeling of Continuum Manipulators Using Ritz and Ritz-Galerkin Methods

To address the challenges with real-time accurate modeling of multi-segment continuum manipulators in the presence of significant external and body loads, we introduce a novel series solution for variable-curvature Cosserat rod static and Lagrangian dynamic method. By combining a modified Lagrange polynomial series solution, based on experimental observations, with Ritz and Ritz-Galerkin methods, the infinite modeling state space of a continuum manipulator is minimized to geometrical position of a handful of physical points (in our case two). As a result, a unified easy to implement vector formalism is proposed for the nonlinear impedance and configuration control. We showed that by considering the mechanical effects of highly elastic axial deformation, the model accuracy is increased up to 6%. The proposed model predicts experimental results with 6-8% (4-6 [mm]) mean error for the Ritz-Galerkin method in static cases and 16-20% (12-14 [mm]) mean error for the Ritz method in dynamic cases, in planar and general 3D motions. Comparing to five different models in the literature, our approximate solution is shown to be more accurate with the smallest possible number of modeling states and suitable for real-time modeling, observation and control applications

A Dynamic Programming Framework for Optimal Planning of Redundant Robots Along Prescribed Paths With Kineto-Dynamic Constraints

Off-line optimal planning of trajectories for redundant robots along prescribed task space paths is usually broken down into two consecutive processes: first, the task space path is inverted to obtain a joint-space path, then, the latter is parametrized with a time law. If the two processes are separated, they cannot optimize the same objective function, ultimately providing sub-optimal results. In this paper, a unified approach is presented where dynamic programming is the underlying optimization technique. Its flexibility allows accommodating arbitrary constraints and objective functions, thus providing a generic framework for optimal planning of real systems. To demonstrate its applicability to a real world scenario, the framework is instantiated for time-optimality. Compared to numerical solvers, the proposed methodology provides visibility of the underlying resolution process, allowing for further analyses beyond the computation of the optimal trajectory. The effectiveness of the framework is demonstrated on a real 7-degrees-of-freedom serial chain. The issues associated with the execution of optimal trajectories on a real controller are also discussed and addressed. The experiments show that the proposed framework is able to effectively exploit kinematic redundancy to optimize the performance index defined at planning level and generate feasible trajectories that can be executed on real hardware with satisfactory results

A Novel Flexible and Steerable Probe for Minimally Invasive Soft Tissue Intervention

Current trends in surgical intervention favour a minimally invasive (MI) approach, in which complex procedures are performed through increasingly small incisions. Specifically, in neurosurgery, there is a need for minimally invasive keyhole access, which conflicts with the lack of maneuverability of conventional rigid instruments. In an attempt to address this fundamental shortcoming, this thesis describes the concept design, implementation and experimental validation of a novel flexible and steerable probe, named “STING” (Soft Tissue Intervention and Neurosurgical Guide), which is able to steer along curvilinear trajectories within a compliant medium. The underlying mechanism of motion of the flexible probe, based on the reciprocal movement of interlocked probe segments, is biologically inspired and was designed around the unique features of the ovipositor of certain parasitic wasps. Such insects are able to lay eggs by penetrating different kinds of “host” (e.g. wood, larva) with a very thin and flexible multi-part channel, thanks to a micro-toothed surface topography, coupled with a reciprocating “push and pull” motion of each segment. This thesis starts by exploring these foundations, where the “microtexturing” of the surface of a rigid probe prototype is shown to facilitate probe insertion into soft tissue (porcine brain), while gaining tissue purchase when the probe is tensioned outwards. Based on these findings, forward motion into soft tissue via a reciprocating mechanism is then demonstrated through a focused set of experimental trials in gelatine and agar gel. A flexible probe prototype (10 mm diameter), composed of four interconnected segments, is then presented and shown to be able to steer in a brain-like material along multiple curvilinear trajectories on a plane. The geometry and certain key features of the probe are optimised through finite element models, and a suitable actuation strategy is proposed, where the approach vector of the tip is found to be a function of the offset between interlocked segments. This concept of a “programmable bevel”, which enables the steering angle to be chosen with virtually infinite resolution, represents a world-first in percutaneous soft tissue surgery. The thesis concludes with a description of the integration and validation of a fully functional prototype within a larger neurosurgical robotic suite (EU FP7 ROBOCAST), which is followed by a summary of the corresponding implications for future work

Trajectory Generation for a Multibody Robotic System: Modern Methods Based on Product of Exponentials

This work presents several trajectory generation algorithms for multibody robotic systems based on the Product of Exponentials (PoE) formulation, also known as screw theory. A PoE formulation is first developed to model the kinematics and dynamics of a multibody robotic manipulator (Sawyer Robot) with 7 revolute joints and an end-effector. In the first method, an Inverse Kinematics (IK) algorithm based on the Newton-Raphson iterative method is applied to generate constrained joint-space trajectories corresponding to straight-line and curvilinear motions of the end effector in Cartesian space with finite jerk. The second approach describes Constant Screw Axis (CSA) trajectories which are generated using Machine Learning (ML) and Artificial Neural Networks (ANNs) techniques. The CSA method smooths the trajectory in the Special Euclidean (SE(3)) space. In the third approach, a multi-objective Swarm Intelligence (SI) trajectory generation algorithm is developed, where the IK problem is tackled using a combined SI-PoE ML technique resulting in a joint trajectory that avoids obstacles in the workspace, and satisfies the finite jerk constraint on end-effector while minimizing the torque profiles. The final method is a different approach to solving the IK problem using the Deep Q-Learning (DQN) Reinforcement Learning (RL) algorithm which can generate different joint space trajectories given the Cartesian end-effector path. For all methods above, the Newton-Euler recursive algorithm is implemented to compute the inverse dynamics, which generates the joint torques profiles. The simulated torque profiles are experimentally validated by feeding the generated joint trajectories to the Sawyer robotic arm through the developed Robot Operating System (ROS) - Python environment in the Software Development Kit (SDK) mode. The developed algorithms can be used to generate various trajectories for robotic arms (e.g. spacecraft servicing missions)

Automated NDT inspection for large and complex geometries of composite materials

Large components with complex geometries, made of composite materials, have become very common in modern structures. To cope with future demand projections, it is necessary to overcome the current non-destructive testing (NDT) bottlenecks encountered during the inspection phase of manufacture. This thesis investigates several aspects of the introduction of automation within the inspection process of complex parts. The use of six-axis robots for product inspection and non-destructive testing systems is the central investigation of this thesis. The challenges embraced by the research include the development of a novel controlling approach for robotic manipulators and of novel path-planning strategies. The integration of robot manipulators and NDT data acquisition instruments is optimized. An effective and reliable way to encode the NDT data through the interpolated robot feedback positions is implemented. The viability of the new external control method is evaluated experimentally. The observed maximum position and orientation errors are respectively within 2mm and within 1 degree, over an operating envelope of 3m³. A new software toolbox (RoboNDT), aimed at NDT technicians, has been developed during this work. RoboNDT is intended to transform the robot path-planning problem into an easy step of the inspection process. The software incorporates the novel path-planning algorithms developed during this research and is shaped to overcome practical limitations of current OLP software. The software has been experimentally validated using scans on real high value aerospace components. RoboNDT delivers tool-path errors that are lower than the errors given by commercial off-line path-planning software. For example the variability of the standoff is within 10 mm for the tool-paths created with the commercial software and within 4.5 mm for the RoboNDT tool-paths, over a scanned area of 1.6m². The output of this research was used to support a 3-year industrial project, called IntACom and led by TWI on behalf of major aerospace sponsors. The result is a demonstrator system, currently in use at TWI Technology Centre, which is capable of inspecting complex geometries with high throughput. The IntACom system can scan real components 2.8 times faster than traditional 3-DoF scanners deploying phased-array inspection and 6.7 times faster than commercial gantry systems deploying traditional single-element inspection.Large components with complex geometries, made of composite materials, have become very common in modern structures. To cope with future demand projections, it is necessary to overcome the current non-destructive testing (NDT) bottlenecks encountered during the inspection phase of manufacture. This thesis investigates several aspects of the introduction of automation within the inspection process of complex parts. The use of six-axis robots for product inspection and non-destructive testing systems is the central investigation of this thesis. The challenges embraced by the research include the development of a novel controlling approach for robotic manipulators and of novel path-planning strategies. The integration of robot manipulators and NDT data acquisition instruments is optimized. An effective and reliable way to encode the NDT data through the interpolated robot feedback positions is implemented. The viability of the new external control method is evaluated experimentally. The observed maximum position and orientation errors are respectively within 2mm and within 1 degree, over an operating envelope of 3m³. A new software toolbox (RoboNDT), aimed at NDT technicians, has been developed during this work. RoboNDT is intended to transform the robot path-planning problem into an easy step of the inspection process. The software incorporates the novel path-planning algorithms developed during this research and is shaped to overcome practical limitations of current OLP software. The software has been experimentally validated using scans on real high value aerospace components. RoboNDT delivers tool-path errors that are lower than the errors given by commercial off-line path-planning software. For example the variability of the standoff is within 10 mm for the tool-paths created with the commercial software and within 4.5 mm for the RoboNDT tool-paths, over a scanned area of 1.6m². The output of this research was used to support a 3-year industrial project, called IntACom and led by TWI on behalf of major aerospace sponsors. The result is a demonstrator system, currently in use at TWI Technology Centre, which is capable of inspecting complex geometries with high throughput. The IntACom system can scan real components 2.8 times faster than traditional 3-DoF scanners deploying phased-array inspection and 6.7 times faster than commercial gantry systems deploying traditional single-element inspection

TMTDyn: A Matlab package for modeling and control of hybrid rigid–continuum robots based on discretized lumped systems and reduced-order models

A reliable, accurate, and yet simple dynamic model is important to analyzing, designing, and controlling hybrid rigid–continuum robots. Such models should be fast, as simple as possible, and user-friendly to be widely accepted by the evergrowing robotics research community. In this study, we introduce two new modeling methods for continuum manipulators: a general reduced-order model (ROM) and a discretized model with absolute states and Euler–Bernoulli beam segments (EBA). In addition, a new formulation is presented for a recently introduced discretized model based on Euler–Bernoulli beam segments and relative states (EBR). We implement these models in a Matlab software package, named TMTDyn, to develop a modeling tool for hybrid rigid–continuum systems. The package features a new high-level language (HLL) text-based interface, a CAD-file import module, automatic formation of the system equation of motion (EOM) for different modeling and control tasks, implementing Matlab C-mex functionality for improved performance, and modules for static and linear modal analysis of a hybrid system. The underlying theory and software package are validated for modeling experimental results for (i) dynamics of a continuum appendage, and (ii) general deformation of a fabric sleeve worn by a rigid link pendulum. A comparison shows higher simulation accuracy (8–14% normalized error) and numerical robustness of the ROM model for a system with a small number of states, and computational efficiency of the EBA model with near real-time performances that makes it suitable for large systems. The challenges and necessary modules to further automate the design and analysis of hybrid systems with a large number of states are briefly discussed

TMTDyn: A Matlab package for modeling and control of hybrid rigid-continuum robots based on discretized lumped systems and reduced-order models

A reliable, accurate, and yet simple dynamic model is important to analyzing, designing, and controlling hybrid rigid–continuum robots. Such models should be fast, as simple as possible, and user-friendly to be widely accepted by the ever-growing robotics research community. In this study, we introduce two new modeling methods for continuum manipulators: a general reduced-order model (ROM) and a discretized model with absolute states and Euler–Bernoulli beam segments (EBA). In addition, a new formulation is presented for a recently introduced discretized model based on Euler–Bernoulli beam segments and relative states (EBR). We implement these models in a Matlab software package, named TMTDyn, to develop a modeling tool for hybrid rigid–continuum systems. The package features a new high-level language (HLL) text-based interface, a CAD-file import module, automatic formation of the system equation of motion (EOM) for different modeling and control tasks, implementing Matlab C-mex functionality for improved performance, and modules for static and linear modal analysis of a hybrid system. The underlying theory and software package are validated for modeling experimental results for (i) dynamics of a continuum appendage, and (ii) general deformation of a fabric sleeve worn by a rigid link pendulum. A comparison shows higher simulation accuracy (8–14% normalized error) and numerical robustness of the ROM model for a system with a small number of states, and computational efficiency of the EBA model with near real-time performances that makes it suitable for large systems. The challenges and necessary modules to further automate the design and analysis of hybrid systems with a large number of states are briefly discussed

Creases modelling in meshless methods.

PhD ThesesCreases have been recently employed as a cheap and straightforward solution to complex problems, like manufacturing micro-scale 3D components, generating programmable motions or enhancing the energy storage capabilities of polymerbased materials. In particular, creases creation, post-folding deformation and fracture prevention are of critical importance for the success of novel applications. Creases in plates are jump discontinuities in the rotations, and their mechanical behaviour can be reproduced by a hinge-like approximation knowing two parameters: rest opening angle and fold rotational stiffness. These two physical properties change with the material, plate thickness and folding process. Therefore, in principle, one should measure the rest opening angle and the rotational stiffness for each crease. To reduce the amount of experimental work needed to model folded geometries, we developed an analytical model able to predict these two values knowing the elastoplastic properties of the material. We validated our rest opening angle predictions against experimental results. Furthermore, we implemented the hinge-like approximation in a numerical model employing a meshless discretisation taking advantage of a weight function enrichment. The kinematics description and the definition of the strain are capable to reproduce the mechanical response of plates presenting large curvature and large deformation undergoing large rotations in the three-dimensional space. Domains presenting several randomly oriented creases and creases with variable opening angles are simulated. Finally, we show how the presented approach can simulate self-folding structures and crease-crack interactions

AutoGraff: towards a computational understanding of graffiti writing and related art forms.

The aim of this thesis is to develop a system that generates letters and pictures with a style that is immediately recognizable as graffiti art or calligraphy. The proposed system can be used similarly to, and in tight integration with, conventional computer-aided geometric design tools and can be used to generate synthetic graffiti content for urban environments in games and in movies, and to guide robotic or fabrication systems that can materialise the output of the system with physical drawing media. The thesis is divided into two main parts. The first part describes a set of stroke primitives, building blocks that can be combined to generate different designs that resemble graffiti or calligraphy. These primitives mimic the process typically used to design graffiti letters and exploit well known principles of motor control to model the way in which an artist moves when incrementally tracing stylised letter forms. The second part demonstrates how these stroke primitives can be automatically recovered from input geometry defined in vector form, such as the digitised traces of writing made by a user, or the glyph outlines in a font. This procedure converts the input geometry into a seed that can be transformed into a variety of calligraphic and graffiti stylisations, which depend on parametric variations of the strokes