A self-adjusting active compliance controller for multiple robots handling an object

This paper presents the concept and experimental validation of a self-adjusting active compliance controller for n robots handling its compliant behaviour concerning partly unknown flexible object. The control strategy is based on the decomposition of the 6n-dimensional position/force space and includes a feedforward and feedback level. The feedforward level contains motion coordination, force distribution of external forces, creation of internal forces, and an additional loop adding the elastic displacements due to the applied forces to the planned robot positions. The feedback level is organized in the form of an active compliance control law. For adjusting the controller to the, in general, unknown flexible behaviour, which in practice is the main problem of the controller design, a quasi-static model of the system is derived for different contact cases of the object and a procedure is presented, which by use of this model is capable of determining the compliance of the considered system and therefore of adjusting the controller. Experiments with two puma-type robots have been conducted to show the applicability of the self-adjusting control strategy. The task has been to grasp and move an unconstrained object. It is shown, that the system can adjust the control parameters to the unknown system compliance and that the control performance is improved considerably.     

Two strategies of position and force control for two industrial robots handling a single object

The simultaneous position and force control problem for two industrial robots in handling a single object is studied in this paper. Two strategies, position-position control and position-force control, are first proposed. Stability analysis is then conducted for the strategies. Both strategies result in a stable system for simple robotic models. Steady state error is also studied for the strategies. Finally, experimental results are presented to evaluate the two strategies.     

Lyapunov-based control design for multiple robots handling a common object

In this article, we address the problem of controlling multiple robots manipulating a rigid object cooperatively. First we propose and prove a few fundamental properties of the multirobot dynamical system. These properties are then exploited to design aset point regulation controller. The proposed controller takes into account the dynamics of both the object and the manipulators. This controller enables us to control the position of the object and the internal forces acting on the object. An adaptive version of the proposed controller is then introduced. The adaptive controller is able to account for the uncertainty in the mass of the load while ensuring the asymptotic convergence of the load position and the internal forces to their desired values.     

Control of an object with parallel surfaces by a pair of finger robots without object sensing

This paper proposes a method for controlling an object with parallel surfaces in a horizontal plane by a pair of finger robots. The control method can achieve stable grasping, relative orientation control, and relative position control of the grasped object. The control inputs require neither any object parameters nor any object sensing, such as tactile sensors, force sensors, or visual sensors. The control inputs are also quite simple and do not need to solve either inverse kinematics or inverse dynamics. The stability of the closed-loop system is proved, and simulation and experimental results validate the control method.     

Coordinated transportation of a single object by two nonholonomic mobile robots

We propose a decentralized control algorithm for transporting a single object by two nonholonomic mobile robots. One of the robots acts as a leader, whose trajectory is planned by itself or defined previously, whereas the other robot, referred to as a follower, follows the leader by keeping a constant distance from the leader. The follower can also avoid obstacles while following the leader without any absolute information about their position. Furthermore, the two mobile robots can realize an omnidirectional motion of the object when the leader broadcasts some simple information to the follower. Some simulation results show a good performance by the proposed decentralized control algorithm. This work was presented, in part, at the Seventh International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002.     

Solving function distribution and behavior design problem for cooperative object handling by multiple mobile robots

This paper addresses the function distribution and behavior design problem for a multirobot system which incorporates a behavior-based dynamic cooperation strategy for object handling. The proposed multiple robot system is composed of a managing robot and homogeneous behavior-based robots. The cooperation strategy in this system is realized in two steps: designing the distributed robot's cooperative behavioral attributes according to the robot's abilities, and organizing these behavioral attributes so that team cooperation is realized. For indicating an incremental style of local behavior construction, an advanced design of cooperative behavior for coping with unknown disturbance is addressed. Additionally, two extended cooperation strategies designed for a path tracking task are described. These three strategies are based on the same concept on performing manipulation in coordination. Therefore, by considering the function distribution among the managing robot and worker robots, and considering behavior design of each worker robot, the proposed system is able to achieve the object handling task with different performances according to the task requirement, such as with or without path tracking and with or without contact with the environment. Experimental results demonstrate the applicability of the proposed system.     

Estimation of parameters of two coupled maneuvers performed by an active space object

The paper is devoted to the problem of estimating the parameters of two maneuvers performed by an active space object between two successive sessions of measurements, which is very important for the maintenance of the catalog of space objects. The parameters of coplanar and noncoplanar impulse and long-duration maneuvers are determined. An advantage of the proposed method is the high speed of estimation, unattainable in traditional approaches, and simplicity of program implementation, because the solution of each problem depends upon the solution of the preceding, simpler problems.     

智能空间中的服务机器人路径规划

为了加深服务机器人对环境的理解,实现安全高效的智能空间导航,建立了一种信息更为丰富的环境模型——危险度地图;并针对智能空间环境部分未知的特点,设计了分层的路径规划方法.静态规划层根据已知环境信息,采用改进的粒子群优化算法规划初始最优路径,动态规划层利用基于动态危险度地图的改进A＊算法进行避障.该方法克服了常规算法只追求路径最短的缺点,增加了对路径危险度的评价,规划出的路径既安全又较短;且该方法实现简单,实时性好.仿真结果验证了该方案的可行性.     

Cognitive maps for mobile robots—an object based approach

Robots are rapidly evolving from factory work-horses to robot-companions. The future of robots, as our companions, is highly dependent on their abilities to understand, interpret and represent the environment in an efficient and consistent fashion, in a way that is comprehensible to humans. The work presented here is oriented in this direction. It suggests a hierarchical probabilistic representation of space that is based on objects. A global topological representation of places with object graphs serving as local maps is proposed. The work also details the first efforts towards conceptualizing space on the basis of the human compatible representation so formed. Such a representation and the resulting conceptualization would be useful for enabling robots to be cognizant of their surroundings. Experiments on place classification and place recognition are reported in order to demonstrate the applicability of such a representation towards understanding space and thereby performing spatial cognition. Further, relevant results from user studies validating the proposed representation are also reported. Thus, the theme of the work is — representation for spatial cognition.     

Autonomic architecture for fault handling in mobile robots

Innovations in Systems and Software Engineering - This paper describes a generic autonomic architecture for use in developing systems for managing hardware faults in mobile robots. The method by...     

基于虚拟现实的无时延感空间机器人遥控操作研究*

主要研究了克服空间机器人遥控操作时延问题的虚拟建模和仿真技术。首先概述了遥操作时延问题的研究现状;然后提出了一种基于虚拟现实预显示技术解决时延问题的方案;最后开发了基于虚拟现实的无时延感的遥控操作系统,并进行了仿真实验研究。仿真结果表明,虚拟现实技术在有效克服空间机器人遥控操作大时延中发挥了重要作用。     

Asymptotic convergence of an SMO algorithm without any assumptions

The asymptotic convergence of C.-J. Lin (2001) can be applied to a modified SMO (sequential minimal optimization) algorithm by S.S. Keerthi et al. (2001) with some assumptions. The author shows that for this algorithm those assumptions are not necessary.     

Scalable multi-radio communication in modular robots

Decentralized control of self-reconfiguring modular robots requires reliable inter-module communication. Communication links must tolerate module misalignment and implement the neighbor-to-neighbor communication model. In this paper, we propose a wireless system based on multiple radios per module that addresses these challenges. Although the capacity of general wireless mesh networks is known to rapidly decrease with network size, we show that a multi-radio single-channel system has constant capacity in square and cubic lattices of infinite size. We validate the performance of such a system in a testbed with 15 unactuated modules using synthetic data and a benchmark decentralized algorithm. We also demonstrate automatic neighbor detection. The main benefits of radio communication in modular robots are tolerance to module misalignment and to eliminate the tight coupling between communication and mechanical design necessitated by typical existing infrared and wired systems. Our results are the first to establish the feasibility of radio as the primary means of inter-module communication in modular robots.     

运动目标跟踪系统的遮挡问题处理

遮挡是运动目标跟踪研究中的一个重要问题,介绍了基于Markov Chain Monte Carlo(MCMC)的运动物体遮挡问题解决方法.该方法通过建立贝叶斯模型,确定先验概率和条件概率,将车辆分割问题看成求后验概率最大时的车辆状态;然后运用MCMC方法对后验概率进行估计,设计MCMC标准对后验概率进行采样,用长方形模型来近似车辆外形.实验证明MCMC方法在不需对车辆单独初始化的前提下能有效的将相互遮挡的车辆分割出来,检测出车辆之间的相互遮挡.     

Evaluating computation/communication balance in an object recognition task

I present performance measurements for some compute- and communications-intensive image processing tasks required by an object recognition application. The application was implemented as a task farm on a network of transputers, which still are one of the cleanest and best-balanced building blocks for parallel systems. I report on relevant properties of the basic algorithms the application is comprised of; some relevant details of the task farm software; performance measurements on a range of system sizes for tasks of very different granularity and characteristics (including broadcast of global data) with measured loads on processors and communications links; and the detrimental effects on performance of hardware variants that increase communications latency and reduce available bandwidth. The measurements show that for some of the image processing tasks, the transputer system is `on the edge' with respect to available bandwidth and latency. Some possible improvements to the communications infrastructure are discussed in light of these results. Finally, current approaches to affordable parallel computing, such as networks or clusters of workstations, are put into perspective by comparing them with the transputer system, using computation/communication balance as a figure of merit for the comparison. This shows that for current microprocessors, even their pin bandwidth is not sufficient to sustain equivalent (scaled) performance for this typical image processing application; any multiprocessor system built with current networking hardware is so unbalanced compared to the transputer system that it will be severely limited by communications bandwidth and latency.     

Tracking in object action space

In this paper we focus on the joint problem of tracking humans and recognizing human action in scenarios such as a kitchen scenario or a scenario where a robot cooperates with a human, e.g., for a manufacturing task. In these scenarios, the human directly interacts with objects physically by using/manipulating them or by, e.g., pointing at them such as in “Give me that…”. To recognize these types of human actions is difficult because (a) they ought to be recognized independent of scene parameters such as viewing direction and (b) the actions are parametric, where the parameters are either object-dependent or as, e.g., in the case of a pointing direction convey important information. One common way to achieve recognition is by using 3D human body tracking followed by action recognition based on the captured tracking data. For the kind of scenarios considered here we would like to argue that 3D body tracking and action recognition should be seen as an intertwined problem that is primed by the objects on which the actions are applied. In this paper, we are looking at human body tracking and action recognition from a object-driven perspective. Instead of the space of human body poses we consider the space of the object affordances, i.e., the space of possible actions that are applied on a given object. This way, 3D body tracking reduces to action tracking in the object (and context) primed parameter space of the object affordances. This reduces the high-dimensional joint-space to a low-dimensional action space. In our approach, we use parametric hidden Markov models to represent parametric movements; particle filtering is used to track in the space of action parameters. We demonstrate its effectiveness on synthetic and on real image sequences using human-upper body single arm actions that involve objects.     

Identification and tracking of robots in an intelligent space using static cameras and an XPFCP

This paper tackles the problem of identification and tracking of multiple robots in an intelligent space using an array of cameras placed in fixed positions within the environment. Several types of agent can be found in an intelligent space: controlled agents (mobile robots) and uncontrolled ones (users and obstacles). The information transferred between the controlled agents and the intelligent space is limited to the control commands sent to the robots and the measurements of the odometers received from the robots. The proposed solution allows the localization of mobile agents, even if they are not robots; however, we have focused on the controlled agents. The proposal does not require prior knowledge or invasive landmarks on board the robots. It starts from the segmentation of different agents in motion that allows obtaining the boundaries of all robots and an estimation of all 3D points that define those boundaries. Then, the identification of the robots is obtained by comparing the components of the linear velocity estimated by the motion segmentation algorithm and received from the odometers. In order to track the robots, an eXtended Particle Filter with Classification Process (XPFCP) is employed. Several experimental tests have been carried out, and the results obtained validate the proposal.     

LOGUE: an architecture for task and behavior object transmission among multiple autonomous robots

This paper proposes a new communication and control architecture which improves the capability and the flexibility of multiple autonomous robot systems in performing a complicated task and coping with unpredictable situations. This system treats robot’s information as a Behavior Element Object (BEO) and a Task Object (TO) in terms of Object Oriented paradigm. Both BEO and TO can be serialized, so they can be communicated among the robots and behavior server system in the network. The action manager module, device module, and some checking mechanisms are also designed for executing new TO or BEO sent from other robots or a server system. A simulation and basic experiments are presented for a situation of robots’ relief for an emergency purpose.     

Humans and humanoid social robots in communication contexts

As humanoid social robots are developed rapidly in recent years and experimented in social situations, comparing them to humans provides insights into practical as well as philosophical concerns. This study uses the theoretical framework of communication constraints, derived in human–human communication research, to compare whether people apply social-oriented constraints and task-oriented constraints differently to human targets versus humanoid social robot targets. A total of 230 students from the University of Hawaii at Manoa participated in the study. The participants completed a questionnaire, which determined their concern for the five communication constraints (feelings, non-imposition, disapproval, clarity, and effectiveness) in situations involving humans or robots. The results show people were more concerned with avoiding hurting the human’s feelings, avoiding inconveniencing the human interactive partner, and avoiding being disliked by the human and less concerned with avoiding hurting the robot’s feelings, avoiding inconveniencing the robot partner, and avoiding being disliked by the robot. But people did not differ in their concerns of the two task-oriented constraints (clarity and effectiveness) in response to humans versus humanoid robots. The results of the research suggest that people are more likely to emphasize the social-oriented constraints in communication with humans.     

Learning control of autonomous robots using an instance-based classifier generator in continuous state space

A classifier system for the reinforcement learning control of autonomous mobile robots is proposed. The classifier system contains action selection, rules reproduction, and credit assignment mechanisms. An important feature of the classifier system is that it operates with continuous sensor and action spaces. The system is applied to the control of mobile robots. The local controllers use independent classifiers specified at the wheel-level. The controllers work autonomously, and with respect to each other represent dynamic systems connected through the external environment. The feasibility of the proposed system is tested in an experiment with a Khepera robot. It is shown that some patterns of global behavior can emerge from locally organized classifiers. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998