982 resultados para Robots submarins


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The adaptation of robots to changing tasks has been explored in modular self-reconfigurable robot research, where the robot structure is altered by adapting the connectivity of its constituent modules. As these modules are generally complex and large, an upper bound is imposed on the resolution of the built structures. Inspired by growth of plants or animals, robotic body extension (RBE) based on hot melt adhesives allows a robot to additively fabricate and assemble tools, and integrate them into its own body. This enables the robot to achieve tasks which it could not achieve otherwise. The RBE tools are constructed from hot melt adhesives and therefore generally small and only passive. In this paper, we seek to show physical extension of a robotic system in the order of magnitude of the robot, with actuation of integrated body parts, while maintaining the ability of RBE to construct parts with high resolution. Therefore, we present an enhancement of RBE based on hot melt adhesives with modular units, combining the flexibility of RBE with the advantages of simple modular units. We explain the concept of this new approach and demonstrate with two simple unit types, one fully passive and the other containing a single motor, how the physical range of a robot arm can be extended and additional actuation can be added to the robot body. © 2012 IEEE.

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This study presents a novel approach to the design of low-cost and energy-efficient hopping robots, which makes use of free vibration of an elastic curved beam. We found that a hopping robot could benefit from an elastic curved beam in many ways such as low manufacturing cost, light body weight and small energy dissipation in mechanical interactions. A challenging problem of this design strategy, however, lies in harnessing the mechanical dynamics of free vibration in the elastic curved beam: because the free vibration is the outcome of coupled mechanical dynamics between actuation and mechanical structures, it is not trivial to systematically design mechanical structures and control architectures for stable locomotion. From this perspective, this paper investigates a case study of simple hopping robot to identify the design principles of mechanics and control. We developed a hopping robot consisting of an elastic curved beam and a small rotating mass, which was then modeled and analyzed in simulation. The experimental results show that the robot is capable of exhibiting stable hopping gait patterns by using a small actuation with no sensory feedback owing to the intrinsic stability of coupled mechanical dynamics. Furthermore, an additional analysis shows that, by exploiting free vibration of the elastic curved beam, cost of transport of the proposed hopping locomotion can be in the same rage of animals' locomotion including human running. © 2011 IEEE.

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In recent years, there has been increasing interest in the study of gait patterns in both animals and robots, because it allows us to systematically investigate the underlying mechanisms of energetics, dexterity, and autonomy of adaptive systems. In particular, for morphological computation research, the control of dynamic legged robots and their gait transitions provides additional insights into the guiding principles from a synthetic viewpoint for the emergence of sensible self-organizing behaviors in more-degrees-of-freedom systems. This article presents a novel approach to the study of gait patterns, which makes use of the intrinsic mechanical dynamics of robotic systems. Each of the robots consists of a U-shaped elastic beam and exploits free vibration to generate different locomotion patterns. We developed a simplified physics model of these robots, and through experiments in simulation and real-world robotic platforms, we show three distinctive mechanisms for generating different gait patterns in these robots.

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Due to technological limitations, robot actuators are often designed for specific tasks with narrow performance goals, whereas a wide range of behaviors is necessary for autonomous robots in uncertain complex environments. In an effort to increase the versatility of actuators, we introduce a new concept of multimodal actuation (MMA) that employs dynamic coupling in the form of clutches and brakes to change its mode of operation. The dynamic coupling allows motors and passive elements such as springs to be engaged and disengaged within a single actuator. We apply the concept to a linear series elastic actuator which uses friction brakes controlled online for the dynamic coupling. With this prototype, we are able to demonstrate several modes of operation including stiff position control, series elastic actuation as well as the possibility to store and release energy in a controlled manner for explosive tasks such as jumping. In this paper, we model the proposed concept of actuation and show a systematic performance analysis of the physical prototype that we developed in our laboratory. © 1996-2012 IEEE.

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Due to technological limitations robot actuators are often designed for specific tasks with narrow performance goals, whereas a wide range of output and behaviours is necessary for robots to operate autonomously in uncertain complex environments. We present a design framework that employs dynamic couplings in the form of brakes and clutches to increase the performance and diversity of linear actuators. The couplings are used to switch between a diverse range of discrete modes of operation within a single actuator. We also provide a design solution for miniaturized couplings that use dry friction to produce rapid switching and high braking forces. The couplings are designed so that once engaged or disengaged no extra energy is consumed. We apply the design framework and coupling design to a linear series elastic actuator (SEA) and show that this relatively simple implementation increases the performance and adds new behaviours to the standard design. Through a number of performance tests we are able to show rapid switching between a high and a low impedance output mode; that the actuator's spring can be charged to produce short bursts of high output power; and that the actuator has additional passive and rigid modes that consume no power once activated. Robots using actuators from this design framework would see a vast increase in their behavioural diversity and improvements in their performance not yet possible with conventional actuator design. © 2012 IEEE.

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In order to understand the underlying mechanisms of animals' agility, dexterity and efficiency in motor control, there has been an increasing interest in the study of gait patterns in biological and artificial legged systems. This paper presents a novel approach to the study of gait patterns which makes use of intrinsic mechanical dynamics of robotic systems. Each of these robots consists of a U-shape elastic beam and exploits free vibration to generate different gait patterns. We developed a conceptual model for these robots, and through simulation and real-world experiments, we show three distinct mechanisms for generating four different gait patterns in these robots. © 2012 IEEE.

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THERE ARE MANY different kinds of robots: factory automation systems that weld and assemble car engines; machines that place chocolates into boxes; medical devices that support surgeons in operations requiring high-precision manipulation; cars that drive automatically over long distances; vehicles for planetary exploration; mechanisms for powerline or oil platform inspection; toys and educational toolkits for schools and universities; service robots that deliver meals, clean floors, or mow lawns; and "companion robots" that are real partners for humans and share our daily lives. In a sense, all these robots are inspired by biological systems; it's just a matter of degree. A driverless vehicle imitates animals moving autonomously in the world.© 2012 ACM.

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The discipline of Artificial Intelligence (AI) was born in the summer of 1956 at Dartmouth College in Hanover, New Hampshire. Half of a century has passed, and AI has turned into an important field whose influence on our daily lives can hardly be overestimated. The original view of intelligence as a computer program - a set of algorithms to process symbols - has led to many useful applications now found in internet search engines, voice recognition software, cars, home appliances, and consumer electronics, but it has not yet contributed significantly to our understanding of natural forms of intelligence. Since the 1980s, AI has expanded into a broader study of the interaction between the body, brain, and environment, and how intelligence emerges from such interaction. This advent of embodiment has provided an entirely new way of thinking that goes well beyond artificial intelligence proper, to include the study of intelligent action in agents other than organisms or robots. For example, it supplies powerful metaphors for viewing corporations, groups of agents, and networked embedded devices as intelligent and adaptive systems acting in highly uncertain and unpredictable environments. In addition to giving us a novel outlook on information technology in general, this broader view of AI also offers unexpected perspectives into how to think about ourselves and the world around us. In this chapter, we briefly review the turbulent history of AI research, point to some of its current trends, and to challenges that the AI of the 21st century will have to face. © Springer-Verlag Berlin Heidelberg 2007.

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It has long been the dream to build robots which could walk and run with ease. To date, the stance phase of walking robots has been characterized by the use of either straight, rigid legs, as is the case of passive walkers, or by the use of articulated, kinematically-driven legs. In contrast, the design of most hopping or running robots is based on compliant legs which exhibit quite natural behavior during locomotion. © 2006 Springer.

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There is much to gain from providing walking machines with passive dynamics, e.g. by including compliant elements in the structure. These elements can offer interesting properties such as self-stabilization, energy efficiency and simplified control. However, there is still no general design strategy for such robots and their controllers. In particular, the calibration of control parameters is often complicated because of the highly nonlinear behavior of the interactions between passive components and the environment. In this article, we propose an approach in which the calibration of a key parameter of a walking controller, namely its intrinsic frequency, is done automatically. The approach uses adaptive frequency oscillators to automatically tune the intrinsic frequency of the oscillators to the resonant frequency of a compliant quadruped robot The tuning goes beyond simple synchronization and the learned frequency stays in the controller when the robot is put to halt. The controller is model free, robust and simple. Results are presented illustrating how the controller can robustly tune itself to the robot, as well as readapt when the mass of the robot is changed. We also provide an analysis of the convergence of the frequency adaptation for a linearized plant, and show how that analysis is useful for determining which type of sensory feedback must be used for stable convergence. This approach is expected to explain some aspects of developmental processes in biological and artificial adaptive systems that "develop" through the embodied system-environment interactions. © 2006 IEEE.

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Exploiting the body dynamics to control the behavior of robots is one of the most challenging issues, because the use of body dynamics has a significant potential in order to enhance both complexity of the robot design and the speed of movement. In this paper, we explore the control strategy of rapid four-legged locomotion by exploiting the intrinsic body dynamics. Based on the fact that a simple model of four-legged robot is known to exhibit interesting locomotion behavior, this paper analyzes the characteristics of the dynamic locomotion for the purpose of the locomotion control. The results from a series of running experiments with a robot show that, by exploiting the unique characteristics induced by the body dynamics, the forward velocity can be controlled by using a very simple method, in which only one control parameter is required. Furthermore it is also shown that a few of such different control parameters exist, each of them can control the forward velocity. Interestingly, with these parameters, the robot exhibits qualitatively different behavior during the locomotion, which could lead to our comprehensive understanding toward the behavioral diversity of adaptive robotic systems. © 2005 IEEE.

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Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

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通过分析基于模型的补偿方法和非模型补偿方法的优缺点,结合一个五轴磨抛机器人的结构特点,提出了两种补偿方法相结合的混合补偿算法.针对平移关节误差的主要来源难于建模的特点,采用非模型的方法进行补偿;针对转动关节误差主要来源为几何参数误差,能够建模,但有些参数随机器人末端位置不同而变化的特点,采用二者相结合的混合方法进行补偿.通过对该机器人系统的实验,验证了方法的有效性和可行性.

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针对势场法的障碍物附近目标不可达(GNRON)问题,采用改进斥力势场函数,把机器人和目标的相对距离考虑进去,从而确保目标点为整个势场的全局最小点,使得机器人能够顺利到达目标。针对局部极小引起的陷阱区域问题,提出了增加引导点的方法,使得机器人能够快速走出陷阱区域,向目标点移动。通过仿真实验,还实现了机器人在限定区域内漫游。改进后的势场法适用于复杂环境下的移动机器人路径规划。仿真结果证明了此方法的有效性。

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本文设计了研磨抛光机器人运动控制器的核心硬件结构和软件模块,采用了参数模糊自整定PID机器人关节位置控制策略,通过实验表明该运动控制器可以大大降低研磨抛光机器人的位置跟踪误差。建立的模块化的软件体系,便于运动控制器的维护和扩展,并可将其应用到其它工业机器人上。