Impact of hybrid surfaces on the droplet breakup dynamics in microgravity slug flow: A dynamic contact angle analysis

Microfluidic devices, which enable precise control and manipulation of fluids at the microscale, have revolutionized various fields, including chemical synthesis and space technology. A comprehensive understanding of fluid behavior under diverse conditions, particularly in microgravity, is essential for optimizing the design and performance of these devices. This paper aims to investigate the effects of discontinuous wettability on droplet breakup structures under microgravity conditions using a microchannel wall. The approach we adopt is underpinned by the volume-of-fluid methodology, an efficient technique renowned for its accurate resolution of the fluid interface in a two-phase flow. Furthermore, a modified dynamic contact angle model is employed to precisely predict the shape of the droplet interface at and near the wall. Our comprehensive model considers influential parameters such as slug length and droplet generation frequency, thereby providing crucial insights into their impact on the two-phase interface velocity. Validated against existing literature data, our model explores the impact of various configurations of discontinuous wettability on breakup morphology. Our findings highlight the significance of employing a dynamic contact angle methodology for making accurate predictions of droplet shape, which is influenced by the wall contact angle. Emphasis is placed particularly on the effects of slug length and droplet generation frequency. Notably, we demonstrate that the use of a hybrid surface at the junction section allows for precise control over the shape and size of the daughter droplets, contrasting with the symmetrical division observed on uniformly hydrophilic or superhydrophobic surfaces. This study contributes valuable insights into the complex dynamics of the droplet breakup process, which has profound implications for the design and optimization of microfluidic devices operating under microgravity conditions. Such insights are further poised to augment applications in space exploration, microreactors, and more

Analyzing Whole-Body Pose Transitions in Multi-Contact Motions

When executing whole-body motions, humans are able to use a large variety of support poses which not only utilize the feet, but also hands, knees and elbows to enhance stability. While there are many works analyzing the transitions involved in walking, very few works analyze human motion where more complex supports occur. In this work, we analyze complex support pose transitions in human motion involving locomotion and manipulation tasks (loco-manipulation). We have applied a method for the detection of human support contacts from motion capture data to a large-scale dataset of loco-manipulation motions involving multi-contact supports, providing a semantic representation of them. Our results provide a statistical analysis of the used support poses, their transitions and the time spent in each of them. In addition, our data partially validates our taxonomy of whole-body support poses presented in our previous work. We believe that this work extends our understanding of human motion for humanoids, with a long-term objective of developing methods for autonomous multi-contact motion planning.Comment: 8 pages, IEEE-RAS International Conference on Humanoid Robots (Humanoids) 201

Modelling and Interactional Control of a Multi-fingered Robotic Hand for Grasping and Manipulation.

PhDIn this thesis, the synthesis of a grasping and manipulation controller of the Barrett hand, which is an archetypal example of a multi-fingered robotic hand, is investigated in some detail. This synthesis involves not only the dynamic modelling of the robotic hand but also the control of the joint and workspace dynamics as well as the interaction of the hand with object it is grasping and the environment it is operating in. Grasping and manipulation of an object by a robotic hand is always challenging due to the uncertainties, associated with non-linearities of the robot dynamics, unknown location and stiffness parameters of the objects which are not structured in any sense and unknown contact mechanics during the interaction of the hand’s fingers and the object. To address these challenges, the fundamental task is to establish the mathematical model of the robot hand, model the body dynamics of the object and establish the contact mechanics between the hand and the object. A Lagrangian based mathematical model of the Barrett hand is developed for controller implementation. A physical SimMechanics based model of the Barrett hand is also developed in MATLAB/Simulink environment. A computed torque controller and an adaptive sliding model controller are designed for the hand and their performance is assessed both in the joint space and in the workspace. Stability analysis of the controllers are carried out before developing the control laws. The higher order sliding model controllers are developed for the position control assuming that the uncertainties are in place. Also, this controllers enhance the performance by reducing chattering of the control torques applied to the robot hand. A contact model is developed for the Barrett hand as its fingers grasp the object in the operating environment. The contact forces during the simulation of the interaction of the fingers with the object were monitored, for objects with different stiffness values. Position and force based impedance controllers are developed to optimise the contact force. To deal with the unknown stiffness of the environment, adaptation is implemented by identifying the impedance. An evolutionary algorithm is also used to estimate the desired impedance parameters of the dynamics of the coupled robot and compliant object. A Newton-Euler based model is developed for the rigid object body. A grasp map and a hand Jacobian are defined for the Barrett hand grasping an object. A fixed contact model with friction is considered for the grasping and the manipulation control. The compliant dynamics of Barrett hand and object is developed and the control problem is defined in terms of the contact force. An adaptive control framework is developed and implemented for different grasps and manipulation trajectories of the Barrett hand. The adaptive controller is developed in two stages: first, the unknown robot and object dynamics are estimated and second, the contact force is computed from the estimated dynamics. The stability of the controllers is ensured by applying Lyapunov’s direct method

A Whole-Body Pose Taxonomy for Loco-Manipulation Tasks

Exploiting interaction with the environment is a promising and powerful way to enhance stability of humanoid robots and robustness while executing locomotion and manipulation tasks. Recently some works have started to show advances in this direction considering humanoid locomotion with multi-contacts, but to be able to fully develop such abilities in a more autonomous way, we need to first understand and classify the variety of possible poses a humanoid robot can achieve to balance. To this end, we propose the adaptation of a successful idea widely used in the field of robot grasping to the field of humanoid balance with multi-contacts: a whole-body pose taxonomy classifying the set of whole-body robot configurations that use the environment to enhance stability. We have revised criteria of classification used to develop grasping taxonomies, focusing on structuring and simplifying the large number of possible poses the human body can adopt. We propose a taxonomy with 46 poses, containing three main categories, considering number and type of supports as well as possible transitions between poses. The taxonomy induces a classification of motion primitives based on the pose used for support, and a set of rules to store and generate new motions. We present preliminary results that apply known segmentation techniques to motion data from the KIT whole-body motion database. Using motion capture data with multi-contacts, we can identify support poses providing a segmentation that can distinguish between locomotion and manipulation parts of an action.Comment: 8 pages, 7 figures, 1 table with full page figure that appears in landscape page, 2015 IEEE/RSJ International Conference on Intelligent Robots and System

Data-Driven Grasp Synthesis - A Survey

We review the work on data-driven grasp synthesis and the methodologies for sampling and ranking candidate grasps. We divide the approaches into three groups based on whether they synthesize grasps for known, familiar or unknown objects. This structure allows us to identify common object representations and perceptual processes that facilitate the employed data-driven grasp synthesis technique. In the case of known objects, we concentrate on the approaches that are based on object recognition and pose estimation. In the case of familiar objects, the techniques use some form of a similarity matching to a set of previously encountered objects. Finally for the approaches dealing with unknown objects, the core part is the extraction of specific features that are indicative of good grasps. Our survey provides an overview of the different methodologies and discusses open problems in the area of robot grasping. We also draw a parallel to the classical approaches that rely on analytic formulations.Comment: 20 pages, 30 Figures, submitted to IEEE Transactions on Robotic

Assembly and force measurement with SPM-like probes in holographic optical tweezers

We report a high fidelity tomographic reconstruction of the quantum state of photon pairs generated by parametric down-conversion with orbital angular momentum (OAM) entanglement. Our tomography method allows us to estimate an upper and lower bound for the entanglement between the down-converted photons. We investigate the two-dimensional state subspace defined by the OAM states ±ℓ and superpositions thereof, with ℓ=1, 2, ..., 30. We find that the reconstructed density matrix, even for OAMs up to around ℓ=20, is close to that of a maximally entangled Bell state with a fidelity in the range between F=0.979 and F=0.814. This demonstrates that, although the single count-rate diminishes with increasing ℓ, entanglement persists in a large dimensional state space