Experimental Investigations of Elastic Tail Propulsion at Low Reynolds Number

A simple way to generate propulsion at low Reynolds number is to periodically oscillate a passive flexible filament. Here we present a macroscopic experimental investigation of such a propulsive mechanism. A robotic swimmer is constructed and both tail shape and propulsive force are measured. Filament characteristics and the actuation are varied and resulting data are quantitatively compared with existing linear and nonlinear theories

Investigation of a novel elastic-mechanical wheel transmission under light duty conditions

A novel 'Elastic Engagement and Friction Coupled' (EEFC) mechanical transmission has been proposed recently in which the power is transmitted through elastic tines on the surfaces of the driving and driven wheels. This study introduces new variations of EEFC mechanical wheel transmission ( broadly emulating a gear-pair) with small contact areas for use under light duty conditions. Because a drive of this type inevitably has a strong statistical component, theoretical analysis of the geometrical and mechanical relationships has been attempted by using linear modeling and empirical weightings. Several simple forms of the EEFC wheel transmission are tested under limiting ( slip) conditions for transmission force and transmission coefficients against normal load. Normalized standard deviation of these parameters is used to summarize noise performance. Models and experiments are in reasonable agreement, suggesting that the model parameters reflect important design considerations. EEFC transmissions appear well suited to force regimes of a few tenths of a newton and to have potential for use in, for example, millimetre-scale robots

Empirical measurements of small unmanned aerial vehicle co-axial rotor systems

Small unmanned aerial vehicles (SUAV) are beginning to dominate the area of intelligence, surveillance, target acquisition and reconnaissance (ISTAR) in forward operating battlefield scenarios. Of particular interest are vertical take-off and landing (VTOL) variants. Within this category co-axial rotor designs have been adopted due to their inherent advantages of size and power to weight ratio. The inter-rotor spacing attribute of a co-axial rotor system appears to offer insight into the optimum design characteristic. The H/D ratio has been cited as a significant factor in many research papers, but to date has lacked an empirical value or an optimal dimensionless condition. In this paper the H/D ratio of a SUAV has been explored thoroughly, reviewing the performance of these systems at incremental stages, the findings from this study have shown that a range of H/D ratios in the region of (0.41-0.65) is advantageous in the performance of SUAV systems. This finding lends itself to the theory of inter-rotor spacing as a non-dimensionally similar figure, which cannot be applied across a spectrum of systems; this could be attributed to the viscous losses of flight at low Reynolds Numbers (< 50,000

Advances in Bio-Inspired Robots

This book covers three major topics, specifically Biomimetic Robot Design, Mechanical System Design from Bio-Inspiration, and Bio-Inspired Analysis on A Mechanical System. The Biomimetic Robot Design part introduces research on flexible jumping robots, snake robots, and small flying robots, while the Mechanical System Design from Bio-Inspiration part introduces Bioinspired Divide-and-Conquer Design Methodology, Modular Cable-Driven Human-Like Robotic Arm andWall-Climbing Robot. Finally, in the Bio-Inspired Analysis on A Mechanical System part, research contents on the control strategy of Surgical Assistant Robot, modeling of Underwater Thruster, and optimization of Humanoid Robot are introduced

The Convergence of Parametric Resonance and Vibration Energy Harvesting

Energy harvesting is an emerging technology that derives electricity from the ambient environment in a decentralised and self-contained fashion. Applications include self-powered medical implants, wearable electronics and wireless sensors for structural health monitoring. Amongst the vast options of ambient sources, vibration energy harvesting (VEH) has attracted by far the most research attention. Two of the key persisting issues of VEH are the limited power density compared to conventional power supplies and confined operational frequency bandwidth in light of the random, broadband and fast-varying nature of real vibration. The convention has relied on directly excited resonance to maximise the mechanical-to-electrical energy conversion efficiency. This thesis takes a fundamentally different approach by employing parametric resonance, which, unlike the former, its resonant amplitude growth does not saturate due to linear damping. Therefore, parametric resonance, when activated, has the potential to accumulate much more energy than direct resonance. The vibrational nonlinearities that are almost always associated with parametric resonance can offer a modest frequency widening. Despite its promising theoretical potentials, there is an intrinsic damping dependent initiation threshold amplitude, which must be attained prior to its onset. The relatively low amplitude of real vibration and the unavoidable presence of electrical damping to extract the energy render the onset of parametric resonance practically elusive. Design approaches have been devised to passively minimise this initiation threshold. Simulation and experimental results of various design iterations have demonstrated favourable results for parametric resonance as well as the various threshold-reduction mechanisms. For instance, one of the macro-scale electromagnetic prototypes (∼1800 cm3) when parametrically driven, has demonstrated around 50% increase in half power band and an order of magnitude higher peak power (171.5 mW at 0.57 ms−2) in contrast to the same prototype directly driven at fundamental resonance (27.75 mW at 0.65 ms−2). A MEMS (micro-electromechanical system) prototype with the additional threshold-reduction design needed 1 ms−2 excitation to activate parametric resonance while a comparable device without the threshold-reduction mechanism required in excess of 30 ms−2. One of the macro-scale piezoelectric prototypes operated into auto-parametric resonance has demon-strated notable further reduction to the initiation threshold. A vacuum packaged MEMS prototype demonstrated broadening of the frequency bandwidth along with higher power peak (324 nW and 160 Hz) for the parametric regime compared to when operated in room pressure (166 nW and 80 Hz), unlike the higher but narrower direct resonant peak (60.9 nW and 11 Hz in vacuum and 20.8 nW and 40 Hz in room pressure). The simultaneous incorporation of direct resonance and bi-stability have been investigated to realise multi-regime VEH. The potential to integrate parametric resonance in the electrical domains have also been numerically explored. The ultimate aim is not to replace direct resonance but rather for the various resonant phenomena to complement each other and together harness a larger region of the available power spectrum

Biologically inspired perching for aerial robots

2021 Spring.Includes bibliographical references.Micro Aerial Vehicles (MAVs) are widely used for various civilian and military applications (e.g., surveillance, search, and monitoring, etc.); however, one critical problem they are facing is the limited airborne time (less than one hour) due to the low aerodynamic efficiency, low energy storage capability, and high energy consumption. To address this problem, mimicking biological flyers to perch onto objects (e.g., walls, power lines, or ceilings) will significantly extend MAVs' functioning time for surveillance or monitoring related tasks. Successful perching for aerial robots, however, is quite challenging as it requires a synergistic integration of mechanical and computational intelligence. Mechanical intelligence means mechanical mechanisms to passively damp out the impact between the robot and the perching object and robustly engage the robot to the perching objects. Computational intelligence means computation algorithms to estimate, plan, and control the robot's motion so that the robot can progressively reduce its speed and adjust its orientation to perch on the objects with a desired velocity and orientation. In this research, a framework for biologically inspired perching is investigated, focusing on both computational and mechanical intelligence. Computational intelligence includes vision-based state estimation and trajectory planning. Unlike traditional flight states such as position and velocity, we leverage a biologically inspired state called time-to-contact (TTC) that represents the remaining time to the perching object at the current flight velocity. A faster and more accurate estimation method based on consecutive images is proposed to estimate TTC. Then a trajectory is planned in TTC space to realize the faster perching while satisfying multiple flight and perching constraints, e.g., maximum velocity, maximum acceleration, and desired contact velocity. For mechanical intelligence, we design, develop, and analyze a novel compliant bistable gripper with two stable states. When the gripper is open, it can close passively by the contact force between the robot and the perching object, eliminating additional actuators or sensors. We also analyze the bistability of the gripper to guide and optimize the design of the gripper. At the end, a customized MAV platform of size 250 mm is designed to combine computational and mechanical intelligence. A Raspberry Pi is used as the onboard computer to do vision-based state estimation and control. Besides, a larger gripper is designed to make the MAV perch on a horizontal rod. Perching experiments using the designed trajectories perform well at activating the bistable gripper to perch while avoiding large impact force which may damage the gripper and the MAV. The research will enable robust perching of MAVs so that they can maintain a desired observation or resting position for long-duration inspection, surveillance, search, and rescue

Empirical measurements of small unmanned aerial vehicle co-axial rotor systems.

Small unmanned aerial vehicles (SUAV) are beginning to dominate the area of intelligence, surveillance, target acquisition and reconnaissance (ISTAR) in forward operating battlefield scenarios. Of particular interest are vertical take-off and landing (VTOL) variants. Within this category co-axial rotor designs have been adopted due to their inherent advantages of size and power to weight ratio. The inter-rotor spacing attribute of a co-axial rotor system appears to offer insight into the optimum design characteristic. The H/D ratio has been cited as a significant factor in many research papers, but to date has lacked an empirical value or an optimal dimensionless condition. In this paper the H/D ratio of a SUAV has been explored thoroughly, reviewing the performance of these systems at incremental stages, the findings from this study have shown that a range of H/D ratios in the region of (0.41-0.65) is advantageous in the performance of SUAV systems. This finding lends itself to the theory of inter-rotor spacing as a non-dimensionally similar figure, which cannot be applied across a spectrum of systems; this could be attributed to the viscous losses of flight at low Reynolds Numbers (< 50,000)

Characterizing motor control signals in the spinal cord

The main goal of this project is to develop a rodent model to study the central command signals generated in the brain and spinal cord for the control of motor function in the forearms. The nature of the central command signal has been debated for many decades with only limited progress. This thesis presents a project that investigated this problem using novel techniques. Rats are instrumented to record the control signals in their spinal cord while they are performing lever press task they are trained in. A haptic interface and wireless neural data amplifier system simultaneously collects dynamic and neural data. Isometric force is predicted from force signal using a combination of time-frequency analysis, Principle component analysis and linear filters. Neural-force mapping obtained at one location are subsequently applied to isometric data recorded at other locations. Prediction errors exhibited negative relationship with the isometric position at upper half of movement range. This suggests the presence of restorative forces which are consistent with positional feedback at spinal level. The animal also appears to become unstable in the lower half of their movement ranges, likely caused by a transition from bipedal to quadruped posture. The presence of local feedback and ability for animals to plan postures that are unstable in absence of external forces suggest that descending signal is a reference trajectory planned using internal models. This has important consequences in design of neuroprosthetic actuators: Inverse dynamic models of patient limbs and local positional feedbacks can improve their performance

Can the self-propulsion of anisotropic microswimmers be described by using forces and torques?

The self-propulsion of artificial and biological microswimmers (i.e., active colloidal particles) has often been modelled by using a force and a torque entering into the overdamped equations for the Brownian motion of passive particles. This seemingly contradicts the fact that a swimmer is force-free and torque-free, i.e., that the net force and torque on the particle vanish. Using different models for mechanical and diffusiophoretic self-propulsion, we demonstrate here that the equations of motion of microswimmers can be mapped onto those of passive particles with the shape-dependent grand resistance matrix and formally external effective forces and torques. This is consistent with experimental findings on the circular motion of artificial asymmetric microswimmers driven by self-diffusiophoresis. The concept of effective self-propulsion forces and torques significantly facilitates the understanding of the swimming paths, e.g., for a microswimmer under gravity. However, this concept has its limitations when the self-propulsion mechanism of a swimmer is disturbed either by another particle in its close vicinity or by interactions with obstacles, such as a wall.Comment: 19 pages, 2 figure

DEVELOPMENT OF A NOVEL Z-AXIS PRECISION POSITIONING STAGE WITH MILLIMETER TRAVEL RANGE BASED ON A LINEAR PIEZOELECTRIC MOTOR

Piezoelectric-based positioners are incorporated into stereotaxic devices for microsurgery, scanning tunneling microscopes for the manipulation of atomic and molecular-scale structures, nanomanipulator systems for cell microinjection and machine tools for semiconductor-based manufacturing. Although several precision positioning systems have been developed for planar motion, most are not suitable to provide long travel range with large load capacity in vertical axis because of their weights, size, design and embedded actuators. This thesis develops a novel positioner which is being developed specifically for vertical axis motion based on a piezoworm arrangement in flexure frames. An improved estimation of the stiffness for Normally Clamped (NC) clamp is presented. Analytical calculations and finite element analysis are used to optimize the design of the lifting platform as well as the piezoworm actuator to provide maximum thrust force while maintaining a compact size. To make a stage frame more compact, the actuator is integrated into the stage body. The complementary clamps and the amplified piezoelectric actuators based extenders are designed such that no power is needed to maintain a fixed vertical position, holding the payload against the force of gravity. The design is extended to a piezoworm stage prototype and validated through several tests. Experiments on the prototype stage show that it is capable of a speed of 5.4 mm/s, a force capacity of 8 N and can travel over 16 mm