BogieBot: A Climbing Robot in Cluttered Confined Space of Bogies with Ferrous Metal Surfaces

Proactive inspection is essential for prediction and prevention of rolling stock component failures. The conventional process for inspecting bogies under trains presents significant challenges for inspectors who need to visually check the tight and cluttered environment. We propose a miniature multi-link climbing robot, called BogieBot, that can be deployed inside the undercarriage areas of trains and other large vehicles for inspection and maintenance purposes. BogieBot can carry a visual sensor or manipulator on its main body. The novel compact design utilises six identical couple joints and two mechanically switchable magnetic grippers that together, empower multi-modal climbing and manipulation. The proposed mechanism is kinematically redundant, allowing the robot to perform self-motions in a tight space and manoeuvre around obstacles. The mechanism design and various analyses on the forward and inverse kinematic, work-space, and self-motions of BogieBot are presented. The robot is demonstrated to perform challenging navigation tasks in different scenarios involving simulated complex environments

Dynamic Modeling, Design and Control of Wire-Borne Underactuated Brachiating Robots: Theory and Application

The ability of mobile robots to locomote safely in unstructured environments will be a cornerstone of robotics of the future. Introducing robots into fully unstructured environments is known to be a notoriously difficult problem in the robotics field. As a result, many of today's mobile robots are confined to prepared level surfaces in laboratory settings or relatively controlled environments only. One avenue for deploying mobile robots into unstructured settings is to utilize elevated wire networks. The research conducted under this thesis lays the groundwork for developing a new class of wire-borne underactuated robots that employs brachiation -- swinging like an ape -- as a means of locomotion on flexible cables. Executing safe brachiation maneuvers with a cable-suspended underactuated robot is a challenging problem due to the complications induced by the cable dynamics and vibrations. This thesis studies, from concept through experiments, the dynamic modeling techniques and control algorithms for wire-borne underactuated brachiating robots, to develop advanced locomotion strategies that enable the robots to perform energy-efficient and robust brachiation motions on flexible cables. High-fidelity and approximate dynamic models are derived for the robot-cable system, which provide the ability to model the interactions between the cable and the robot and to include the flexible cable dynamics in the control design. An optimal trajectory generation framework is presented in which the flexible cable dynamics are explicitly accounted for when designing the optimal swing trajectories. By employing a variety of control-theoretic methods such as robust and adaptive estimation, control Lyapunov and barrier functions, semidefinite programming and sum-of-squares optimization, a set of closed-loop control algorithms are proposed. A novel hardware brachiating robot design and embodiment are presented, which incorporate unique mechanical design features and provide a reliable testbed for experimental validation of the wire-borne underactuated brachiating robots. Extensive simulation results and hardware experiments demonstrate that the proposed multi-body dynamic models, trajectory optimization frameworks, and feedback control algorithms prove highly useful in real world settings and achieve reliable brachiation performance in the presence of uncertainties, disturbances, actuator limits and safety constraints.Ph.D

A toy rock climbing robot

The goal of this thesis was to build a simple toy rock climbing robot, and to explore problems related to grasping, path planning, and robot control. The robot is capable of climbing a wall of pegs either under manual control through a host system and an infrared interface, or on the basis of a set of pre-recorded keyframes. In addition, the robot can climb certain peg configurations using a cyclic gait. The robot climbs in an open-loop mode without sensor feedback. All communications are sent through the IR connection, and the tether to the robot consists only of two power wires

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Shape Modelling of Bones: Application to the Primate Shoulder

The aims of this work were to develop techniques for describing morphological variations of shoulder bones and to test these on real datasets. The robust measurement and description of anatomical geometry can provide accu- rate estimation and better understanding of bone morphology. Feature lines were detected automatically using crest line techniques and shape information from shoulder bones was extracted based on the extracted feature lines. Redefinition of local coordinate systems was proposed utilising the crest line technique. Three dimensional statistical shape models (SSM) were built for a set of primate humeri and scapulae. Two types of models were constructed: one incorporated the main- tained original scale whilst the other used scaled bones. Variations were captured and quantified by Principal Component Analysis (PCA). The application can be extended generally to long bones and other complex bones and was also tested on human femora. Techniques to predict the shape of one bone from its neighbour at a joint were presented. PCA was used to reduce data dimensionality to a few principal components. Canonical Correlation Analysis (CCA) and Partial Least Square (PLS) Regression were applied to explore the linear morphological correlations between the two shoulder bones and to predict the shape of one segment given the shape of the adjoining segment

On the discretisation of actuation in locomotion: Impulse- and shape-based modelling for hopping robots

In an age where computers challenge the smartest human beings in cognitive tasks, the conspicuous discrepancy between robot and animal locomotion appears paradoxical. While animals can move around autonomously in complex environments, today’s robots struggle to independently operate in such surroundings. There are many reasons for robots’ inferior performance, but arguably the most important one is our missing understanding of complexity. This thesis introduces the notion of discrete actuation for the study of locomotion in robots and animals. The actuation of a system with discrete actuation is restricted to be applied at a finite number of instants in time and is impulsive. We find that, despite their simplicity, such systems can predict various experimental observations and inspire novel technologies for robot design and control. We further find that, through the study of discrete actuation, causal relationships between actuation and resulting behaviour are revealed and become quantifiable, which relates the findings presented in this thesis to the broader concepts of complexity, self-organisation, and self-stability. We present four case studies in Chapters 3-6 which demonstrate how the concept of discrete actuation can be employed to understand the physics of locomotion and to facilitate novel robot technologies. We first introduce the impulsive eccentric wheel model which is a discretely actuated system for the study of hopping locomotion. We find that the model predicts robot hopping trajectories and animal related hopping characteristics by reducing the dynamics of hopping–usually described by hybrid differential equations–to analytic maps. The reduction of complexity of the model equations reveals the underlying physics of the locomotion process, and we identify the importance of robot shape and mass distribution for the locomotion performance. As a concrete application of the model, we compare the energetics of hopping and rolling locomotion in environments with obstacles and find when it is better to hop than to roll, based on the fundamental physical principles we discover in the model analysis. The theoretical insights of this modelling approach enable new actuation techniques and design for robots which we display in Robbit; a robot that uses strictly convex foot shapes and rotational impulses to induce hopping locomotion. We show that such systems outperform hopping with non-strictly convex shapes in terms of energy effective and robust locomotion. A system with discrete actuation motivates the exploitation of shape and the environment to improve locomotion dynamics, which reveals advantageous effect of inelastic impacts between the robot foot and the environment. We support this idea with experimental results from the robot CaneBot which can change its foot shape to induce timed impacts with the environment. Even though inelastic impacts are commonly considered detrimental for locomotion dynamics, we show that their appropriate control improves the locomotion speed considerably. The findings presented in this thesis show that discrete actuation for locomotion inspires novel ways to appreciate locomotion dynamics and facilitates unique control and design technologies for robots. Furthermore, discrete actuation emphasises the definition of causality in complex systems which we believe will bring robots closer to the locomotion behaviour of animals, enabling more agile and energy effective robots

Origins of vocal-entangled gesture

Gestures during speaking are typically understood in a representational framework: they represent absent or distal states of affairs by means of pointing, resemblance, or symbolic replacement. However, humans also gesture along with the rhythm of speaking, which is amenable to a non-representational perspective. Such a perspective centers on the phenomenon of vocal-entangled gestures and builds on evidence showing that when an upper limb with a certain mass decelerates/accelerates sufficiently, it yields impulses on the body that cascade in various ways into the respiratory–vocal system. It entails a physical entanglement between body motions, respiration, and vocal activities. It is shown that vocal-entangled gestures are realized in infant vocal–motor babbling before any representational use of gesture develops. Similarly, an overview is given of vocal-entangled processes in non-human animals. They can frequently be found in rats, bats, birds, and a range of other species that developed even earlier in the phylogenetic tree. Thus, the origins of human gesture lie in biomechanics, emerging early in ontogeny and running deep in phylogeny

Analytical Models and Control Design Approaches for a 6 DOF Motion Test Apparatus

Wind tunnels play an indispensable role in the process of aircraft design, providing a test bed to produce valuable, accurate data that can be extrapolated to actual flight conditions. Historically, time-averaged data has made up the bulk of wind tunnel research, but modern flight design necessitates the use of dynamic wind tunnel testing to provide time-accurate data for high frequency motion. This research explores the use of a 6 degree of freedom (DOF) motion test apparatus (MTA) in the form of a robotic arm to allow models inside a subsonic wind tunnel to track prescribed trajectories to obtain time-accurate force and moment coefficients. Specifically, different control laws were designed, simulated, and integrated into a 2 DOF model representative of the elbow pitch and wrist pitch joints of the MTA system to decrease positional tracking error for a desired end-effector trajectory. Stability of the closed-loop systems was proven via Lyapunov analysis for all of the control laws, and the control laws proved to decrease tracking error during the trajectory case studies. An adaptive sliding mode control scheme was chosen as most suitable to simulate on the 6 DOF model due to the small tracking error as compared to the other control schemes and the availability of parameters of the actual MTA system when subject to the time-varying aerodynamics of the wind tunnel