网络环境下基于Agent的多机器人协调与路径规划

本文针对基于Ａｇｅｎｔ的分布协作式多机器人装配系统——ＤＡＭＡＳ的特点，在原有工作的基础上，提出了网络环境下基于Ａｇｅｎｔ的路径规划思想，重新定义Ａｇｅｎｔ各功能模块的内容，建立系统中的通讯机制．同时，介绍了系统进行路径规划的工作过程，给出了路径规划器的规划算法

分布式多机器人装配系统任务合作规划算法研究

:综述了多机器人系统任务规划的研究 ,介绍了基于 Agent的分布协作式多机器人装配系统 ,给出了分布式多机器人系统任务协商规划算法 ,采用了改进的合同网协议方法。针对多机器人任务规划算法的软件实现 ,采用了先进的分布式对象技术 ,介绍了算法的具体实现方法

点焊机器人系统通信接口分析与设计

本文叙述了点焊机器人控制系统与焊接控制系统之间的通讯信号的约定关系，叙述了系统的工作时序．并提出了一种通信接口线路

基于TRIP的JX─2机器人信息系统

本文叙述了ＴＲＩＰ软件的特征，介绍了基于ＴＲＩＰ的ＪＸ－２机器人信息系统的组成、功能、特点及应用

海洋机器人变参数大时延控制系统补偿方法的研究

本文提出一种变参数大时延系统的补偿方法，具有传输滞后系统的幅相频率特性和时域特性，流体动力学变参数的修正方法和具有传输滞后和零阶保持器滞后的补偿仿真。

无缆水下机器人组合导航系统

无缆水下机器人是我国首次开展的高技术课题,组合导航系统是无缆水下机器人研究中的关键部分,本文介绍了多种导航设备同时工作,经过信息综合处理获得高精度导航信息的组合导航系统和组合导航系统中所需要的坐标转换及卡尔曼滤波器的计算,为无缆水下机器人建立一个较理想的导航方式。

一个先进的工业机器人计算机控制系统——ARCS

随着工业机器人及其应用的不断发展,要求一个强有力的计算机系统来控制它的工作,并具有灵活、方便的机器人编程语言.本文系统地介绍了我们自行设计并实现的一个先进的机器人控制系统——ARCS.该系统主要包括两部分:(1)一个实时多任务的机器人控制软件SVAL系统,该系统支持一种通用性较强的机器人编程语言——SVAL语言.(2)一个支持该软件系统工作的、具有开放式结构的硬件环境.ARCS系统具有良好的实时性、可扩展性及基于外部传感器信号进行控制的能力.由于该系统的开放式结构.使其根据不同要求可方便地增删其功能,并可控制不同类型的机器人.我们已成功地实现对PUMA760机器人的控制,并在其上引入了力觉与接近觉的传感器,采样时间可缩短到16ms.一年多的运行结果证明,该系统稳定可靠,性能良好,现在正向产品转化.

角速率陀螺在海洋机器人“海人1号”航向控制中的应用

本文给出“海人1号”航向控制的流体动力学模型、航向控制系统结构,海上实验记录以及角速率陀螺作用原理和分析。这将对从事海洋机器人控制系统的设计研究,有一定的考参值价。

Learning Fine Motion by Markov Mixtures of Experts

Compliant control is a standard method for performing fine manipulation tasks, like grasping and assembly, but it requires estimation of the state of contact between the robot arm and the objects involved. Here we present a method to learn a model of the movement from measured data. The method requires little or no prior knowledge and the resulting model explicitly estimates the state of contact. The current state of contact is viewed as the hidden state variable of a discrete HMM. The control dependent transition probabilities between states are modeled as parametrized functions of the measurement We show that their parameters can be estimated from measurements concurrently with the estimation of the parameters of the movement in each state of contact. The learning algorithm is a variant of the EM procedure. The E step is computed exactly; solving the M step exactly would require solving a set of coupled nonlinear algebraic equations in the parameters. Instead, gradient ascent is used to produce an increase in likelihood.

Planning and Teaching Compliant Motion Strategies

This thesis presents a new high level robot programming system. The programming system can be used to construct strategies consisting of compliant motions, in which a moving robot slides along obstacles in its environment. The programming system is referred to as high level because the user is spared of many robot-level details, such as the specification of conditional tests, motion termination conditions, and compliance parameters. Instead, the user specifies task-level information, including a geometric model of the robot and its environment. The user may also have to specify some suggested motions. There are two main system components. The first component is an interactive teaching system which accepts motion commands from a user and attempts to build a compliant motion strategy using the specified motions as building blocks. The second component is an autonomous compliant motion planner, which is intended to spare the user from dealing with "simple" problems. The planner simplifies the representation of the environment by decomposing the configuration space of the robot into a finite state space, whose states are vertices, edges, faces, and combinations thereof. States are inked to each other by arcs, which represent reliable compliant motions. Using best first search, states are expanded until a strategy is found from the start state to a global state. This component represents one of the first implemented compliant motion planners. The programming system has been implemented on a Symbolics 3600 computer, and tested on several examples. One of the resulting compliant motion strategies was successfully executed on an IBM 7565 robot manipulator.

Standard commercial education robotic platform: intermediate solution to teaching robotics

Teaching robotics to students at the beginning of their studies has become a huge challenge. Simulation environments can be an effective solution to that challenge where students can interact with simulated robots and have the first contact with robotic constraints. From our previous experience with simulation environments it was possible to observe that students with lower background knowledge in robotics where able to deal with a limited number of constraints, implement a simulated robotic platform and study several sensors. The question is: after this first phase what should be the best approach? Should the student start developing their own hardware? Hardware development is a very important part of an engineer's education but it can also be a difficult phase that could lead to discouragement and loss of motivation in some students. Considering the previous constraints and first year engineering students’ high abandonment rate it is important to develop teaching strategies to deal with this problem in a feasible way. The solution that we propose is the integration of a low-cost standard robotic platform WowWee Rovio as an intermediate solution between the simulation phase and the stage where the students can develop their own robots. This approach will allow the students to keep working in robotic areas such as: cooperative behaviour, perception, navigation and data fusion. The propose approach proved to be a motivation step not only for the students but also for the teachers. Students and teachers were able to reach an agreement between the level of demand imposed by the teachers and satisfaction/motivation of the students.

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Disseny d’un comportament en ROS per a mantenir la posició d’un vehicle autònom submarí a partir de referències visuals

En el Centre d'Investigació en Robòtica Submarina (CIRS) de la Universitat de Gironaes disposa de diferents robots submarins els quals utilitzen una arquitectura software anomenada Component Oriented Layered-based Architecture for Autonomy ( COLA2 ), la qual ha estat desenvolupada per estudiants i professors del mateix centre. Per tal de fer aquesta arquitectura més accessible per a professors i estudiant d’altres centres la COLA2 s’està adaptant al Robot Operative System (ROS) que és un framework genèric per al desenvolupament d’aplicacions amb robots. Aquest projecte pretén dissenyar un comportament per al robot Girona500 que estigui desenvolupat dins la versió ROS de l’arquitectura COLA2. El comportament haurà de fer mantenir una determinada posició al robot amb informació visual de la càmera del robot i amb dades de navegació. La tasca de mantenir la posició es de vital importància per a poder realitzar intervencions submarines que requereixen de precisió i, precisament, el medi on es treballa no ajuda

Cooperative transport of extended payloads

In this paper we present experimental results for the dual robot transport of an extended payload. Two robotic rovers that were designed specifically for the extended payload transport task are described. Each rover incorporates a 4-DOF robot arm incorporating three active joints (one of which is a gripper), a passive wrist, and a mobile base which employs a rocker-bogie design. A set of behaviours has been developed to support the performance of the task, integrating simple sensing with controls. We describe the behaviours and their integration within the overall task structure. The experimental results presented focus on the manipulation elements of the task, but incorporate a complete cycle of pick-up, traversal, and putdown.

Integrating the Utkin observer with the unscented Kalman filter

This paper describes the integration of an Utkin observer with the unscented Kalman filter, investigates the performance of the combined observer, termed the unscented Utkin observer, and compares it with an unscented Kalman filter. Simulation tests are performed using a model of a single link robot arm with a revolute elastic joint rotating in a vertical plane. The results indicate that the unscented Utkin observer outperforms the unscented Kalman filter.