Universal Robotic Gripper based on the Jamming of Granular Material

Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shape and surface properties remains, however, challenging. Most current designs are based on the multi-fingered hand, but this approach introduces hardware and software complexities. These include large numbers of controllable joints, the need for force sensing if objects are to be handled securely without crushing them, and the computational overhead to decide how much stress each finger should apply and where. Here we demonstrate a completely different approach to a universal gripper. Individual fingers are replaced by a single mass of granular material that, when pressed onto a target object, flows around it and conforms to its shape. Upon application of a vacuum the granular material contracts and hardens quickly to pinch and hold the object without requiring sensory feedback. We find that volume changes of less than 0.5% suffice to grip objects reliably and hold them with forces exceeding many times their weight. We show that the operating principle is the ability of granular materials to transition between an unjammed, deformable state and a jammed state with solid-like rigidity. We delineate three separate mechanisms, friction, suction and interlocking, that contribute to the gripping force. Using a simple model we relate each of them to the mechanical strength of the jammed state. This opens up new possibilities for the design of simple, yet highly adaptive systems that excel at fast gripping of complex objects.Comment: 10 pages, 7 figure

スケーラブルなマルチエージェント大都市域避難行動シミュレータの自動車の考慮に重点をおいた拡張と適用

学位の種別: 課程博士審査委員会委員 : (主査)東京大学准教授 マッデゲダラ ラリス, 東京大学教授 堀 宗朗, 東京大学教授 大口 敬, 東京大学教授 堀田 昌英, 東京大学准教授 市村 強, 東京大学准教授 柳澤 大地University of Tokyo(東京大学

Determination of the ensemble transition dipole moments of self-assembled quantum dot films by time and angle resolved emission spectroscopy measurements

The spontaneous emission of light in semiconductors is due to the excitonic relaxation process. The emission of light requires a change in the transition dipole matrix of the system. This is captured in terms of the physical quantity called transition dipole moment. The transition dipole moment (TDM) characterizes the line strength of the emission process. TDM is of fundamental importance in emitter-cavity interaction as its magnitude decides the interaction strength of emitters and cavities. In all light emitting devices, the orientation of the transition dipole moments is directly related to the optical power output of the devices. In this manuscript, the basic framework of spontaneous emission and Einstein coefficients is discussed for two level systems. Semiconducting alloyed quantum dots (AQDs) are synthesized in hydrophobic phase. AQDs are used as the experimental two level system. The AQDs are then self-assembled into monolayers by the Langmuir-Schaefer method. The ensemble averaged TDM magnitude and orientation of AQDs are extracted from the time resolved and the angle resolved emission spectroscopy measurements respectively. The procedure for finding out the TDM, described in this manuscript is generalized. The mentioned procedure can be extended to any emitters in hydrophobic phase

Optimality and robustness in path-planning under initial uncertainty

Classical deterministic optimal control problems assume full information about the controlled process. The theory of control for general partially-observable processes is powerful, but the methods are computationally expensive and typically address the problems with stochastic dynamics and continuous (directly unobserved) stochastic perturbations. In this paper we focus on path planning problems which are in between -- deterministic, but with an initial uncertainty on either the target or the running cost on parts of the domain. That uncertainty is later removed at some time $T$, and the goal is to choose the optimal trajectory until then. We address this challenge for three different models of information acquisition: with fixed $T$, discretely distributed and exponentially distributed random $T$. We develop models and numerical methods suitable for multiple notions of optimality: based on the average-case performance, the worst-case performance, the average constrained by the worst, the average performance with probabilistic constraints on the bad outcomes, risk-sensitivity, and distributional-robustness. We illustrate our approach using examples of pursuing random targets identified at a (possibly random) later time $T$.Comment: 24 pages, 14 figures. Keywords: optimal control, path-planning, Hamilton-Jacobi PDEs, uncertainty, robustness, delayed information acquisitio

Interactive Motion Planning for Multi-agent Systems with Physics-based and Behavior Constraints

Man-made entities and humans rely on movement as an essential form of interaction with the world. Whether it is an autonomous vehicle navigating crowded roadways or a simulated pedestrian traversing a virtual world, each entity must compute safe, effective paths to achieve their goals. In addition, these entities, termed agents, are subject to unique physical and behavioral limitations within their environment. For example, vehicles have a finite physical turning radius and must obey behavioral constraints such as traffic signals and rules of the road. Effective motion planning algorithms for diverse agents must account for these physics-based and behavior constraints. In this dissertation, we present novel motion planning algorithms that account for constraints which physically limit the agent and impose behavioral limitations on the virtual agents. We describe representational approaches to capture specific physical constraints on the various agents and propose abstractions to model behavior constraints affecting them. We then describe algorithms to plan motions for agents who are subject to the modeled constraints. First, we describe a biomechanically accurate elliptical representation for virtual pedestrians; we also describe human-like movement constraints corresponding to shoulder-turning and side-stepping in dense environments. We detail a novel motion planning algorithm extending velocity obstacles to generate collisionfree paths for hundreds of elliptical agents at interactive rates. Next, we describe an algorithm to encode dynamics and traffic-like behavior constraints for autonomous vehicles in urban and highway environments. We describe a motion planning algorithm to generate safe, high-speed avoidance maneuvers using a novel optimization function and modified control obstacle formulation, and we also present a simulation framework to evaluate driving strategies. Next, we present an approach to incorporate high-level reasoning to model the motions and behaviors of virtual agents in terms of verbal interactions with other agents or avatars. Our approach leverages natural-language interaction to reduce uncertainty and generate effective plans. Finally, we describe an application of our techniques to simulate pedestrian behaviors for gathering simulated data about loading, unloading, and evacuating an aircraft.Doctor of Philosoph

Practical Considerations and Applications for Autonomous Robot Swarms

In recent years, the study of autonomous entities such as unmanned vehicles has begun to revolutionize both military and civilian devices. One important research focus of autonomous entities has been coordination problems for autonomous robot swarms. Traditionally, robot models are used for algorithms that account for the minimum specifications needed to operate the swarm. However, these theoretical models also gloss over important practical details. Some of these details, such as time, have been considered before (as epochs of execution). In this dissertation, we examine these details in the context of several problems and introduce new performance measures to capture practical details. Specifically, we introduce three new metrics: (1) the distance complexity (reflecting power usage and wear-and-tear of robots), (2) the spatial complexity (reflecting the space needed for the algorithm to work), and (3) local computational complexity (reflecting the computational requirements for each robot in the swarm). We apply these metrics in the study of some well-known and important problems, such as Complete Visibility and Arbitrary Pattern Formation. We also introduce and study a new problem, Doorway Egress, that captures the essence of a swarm’s navigation through restricted spaces. First, we examine the distance and spatial complexity used across a class of Complete Visibility algorithms. Second, we provide algorithms for Complete Visibility on an integer plane, including some that are asymptotically optimal in terms of time, distance complexity, and spatial complexity. Third, we introduce the problem of Doorway Egress and provide algorithms for a variety of robot swarm models with various optimalities. Finally, we provide an optimal algorithm for Arbitrary Pattern Formation on the grid

The development of a scenario independent method for evaluating the evacuation complexity of a building

Over the past two decades, more than 30 evacuation models have been developed to reproduce people’s movement patterns in evacuation. However, evacuation models cannot assess whether one building is better than another in regards to evacuation wayfinding. There exist techniques that attempt to compare different buildings for evacuation complexity. However, these graph measures are primarily used to measure the relative accessibility of different locations in a spatial system and were not generated for the purpose of comparing the complexity of different buildings. Currently only one method exists, Donegan’s method [DT98] [PD96] [DT99], which can be applied to compare building for evacuation ability. However, this technique is severely limited to specific building layouts and only considers connectivity. Taking the Donegan’s method as a first step, this thesis extends this algorithm to obtain a new Distance Graph Method, which considers travel distance as well as being able to be applied to graphs with circuits. Then a further building complexity measures is presented, the Global Complexity (PAT) method. This is shown to be a valid measure which considers additional important factors such as wayfinding time, travel distance and the areas of compartments. The Distance Graph Method and Global Complexity (PAT) methods are based on a room graph representation which does not have the descriptive power to describe the actual routes taken during the wayfinding process. To resolve this drawback a further method is presented which utilises a ‘route-based graph’ that has the ability to represent the real route that an evacuee will take during the wayfinding process. Furthermore the Distance Graph Method and Global Complexity (PAT) methods assume a “worst state” calculation for the nodal information. This means for buildings with more than one exit these methods calculate a global building complexity according to a mathematical formula, which considers all exits separately. To address these problems, the final method, Complexity Time Measure, is presented, which is based around a number of wayfinding behaviour rules over a ‘route-based graph’ representation. This addresses the question: ‘If an occupant is positioned at a random location within a building, on average how long does the occupant need to spend to find an available exit?’ Hence, provides a means to compare complex buildings, with circuits, in relation to evacuation capability

Micromachining

To present their work in the field of micromachining, researchers from distant parts of the world have joined their efforts and contributed their ideas according to their interest and engagement. Their articles will give you the opportunity to understand the concepts of micromachining of advanced materials. Surface texturing using pico- and femto-second laser micromachining is presented, as well as the silicon-based micromachining process for flexible electronics. You can learn about the CMOS compatible wet bulk micromachining process for MEMS applications and the physical process and plasma parameters in a radio frequency hybrid plasma system for thin-film production with ion assistance. Last but not least, study on the specific coefficient in the micromachining process and multiscale simulation of influence of surface defects on nanoindentation using quasi-continuum method provides us with an insight in modelling and the simulation of micromachining processes. The editors hope that this book will allow both professionals and readers not involved in the immediate field to understand and enjoy the topic