工業(yè)機(jī)器人應(yīng)用方案使用安全、動作協(xié)調(diào)準(zhǔn)確性及其與人的協(xié)同作業(yè)

1、robots: A case study ofRobots come into physical contact with humans in both experimental and operational settings. Many potential factors motivate the detection of human contact, ranging from safe robot operation around humans, to robot behaviors that depend on human guidance. This article presents

2、 a review of current research within the field of Tactile Human -Robot Interactions (Tactile HRI) , where physical contact from a human is detected by a robot during the execution or development of robot behaviors. Approaches are presented from two viewpoints: the types of physical interactions that

3、 occur between the human and robot, and the types of sensors used to detect these interactions. We contribute a structure for the categorization of Tactile HRI research within each viewpoint. Tactile sensing techniques are grouped into three categories, according to what covers the sensors: (i) a ha

4、rd shell, (ii) a flexible substrate or (iii) no covering. Three categories of physical HRI likewise are identified, consisting of contact that (i) interferes with robot behavior execution, (ii) contributes to behavior execution and (iii) contributes to behavior development. We populate each category

5、 with the current literature, and furthermore identify the state-of-the-art within categories and promising areas for future research.Robot team coord in ati on using dyn amic role and positi oning assig nment and role based setplaysThe coordination methodologies of CAMBADA, a robotic soccer team de

6、signed to participate in the RoboCup Middle-Size League (MSL), are presented in this paper. The approach, which relies on information sharing and integration within the team, is based on formations, flexible positionings and dynamic role and positioning assignment. Role assignment is carried out loc

7、ally on each robot to increase its reactivity. Positioning assignment is carried out at a lower frequency by a coach agent following a new priority-based algorithm that maintains a competitive formation, covering the most important positionings when malfunctions lead to a reduction of the team size.

8、 Coordinated proceduresfor passing and setplays have also been implemented. With this design, CAMBADA reached the 1st place in RoboCup 2008 and the 3rd place in RoboCup 2009. Competition results and performance measures computed from logs and videos of real competition games are presented and discus

9、sed.Towards cooperation of heterogeneous,autonomoushuma noid and wheeled robotsIn this paper a case study of the cooperation of a strongly heterogeneous autonomous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some redundant abilities

10、is presented. By combining strongly heterogeneous robots the diversity ofachievable tasks increases as the variety of sensing and motion abilities of the robot system is extended, compared to a usually considered team of homogeneous robots. A number of methodologies and technologiesrequired in order

11、 to achieve the long-term goal of cooperation of heterogeneousautonomous robots are discussed, including modeling tasks and robot abilities, task assignment and redistribution, robot behavior modeling and programming,robot middleware and robot simulation.Example solutions and their application to th

12、e cooperation of autonomous wheeled and humanoid robots are presented in this case study. The scenario describes a tightly coupled cooperative task, where the humanoid robot and the wheeled robot track a moving ball, which is to be approached and kicked by thehumanoid robot into a goal. The task can

13、 be fulfilled successfully by combining the abilities of both robots.An overview of dyn amic parameter ide ntificati on of robotsDue to the importance to model-based control, dynamic parameter identification has attracted much attention. However, until now, there is still much work for the identific

14、ation of dynamic parameters to be done. In this paper, an overview is given of the existing work on dynamic parameter identification of serial and parallel robots. The methods for estimating the dynamic parameters are summarized, and the advantages and disadvantages of each method are discussed. The

15、 model to be identified and the trajectory optimization are reviewed. Further, the methods for validating the estimated model are summarized and the application of dynamic parameter identification is mentioned. The results of this review are useful for manufacturers of robots in selecting proper ide

16、ntification method and also for researchers in determining further research areas.Towards modelli ng complex robot trai ning tasks through system ide ntificatio nPrevious research has shown that sensor-motor tasks in mobile robotics applications can be modelledautomatically , using NARMAX system ide

17、ntification, where the sensory perception of the robot is mapped to the desired motor commands using non-linear polynomial functions, resulting in a tight coupling between sensing and acting the robot responds directly to the sensor stimuli without having internal states or memory.However, competenc

18、es such as for instance sequences of actions, where actions depend on each other,require memory and thus a representation of state. In these cases a simple direct link between sensory perception and the motor commands may not be enough to accomplish the desired tasks. The contribution of this paper

19、to knowledge is to show how fundamental, simple NARMAX models of behaviour can be used in a bootstrapping process to generatecomplex behaviours that were so farbeyond reach.We argue that as the complexity of the task increases, it is important to estimate the current state of therobot and integrate

20、this information into the system identification process. To achieve this we propose anovel method which relates distinctive locations in the environment to the state of the robot, using anunsupervised clustering algorithm. Once we estimate the current state of the robot accurately, wecombine the sta

21、te information with the perception of the robot through a bootstrapping method togenerate more complex robot tasks: We obtain a polynomial model which models the complex task as a function of predefined low level sensor-motor controllers and raw sensory data.The proposed method has been used to teac

22、h Scitos G5 mobile robots a number of complex tasks, such as advanced obstacle avoidance, or complex route learning.Modeli ng floor-clea ning coverage performa nces of some domestic mobile robots in|a reduced seen arioIn this paper, floor-cleaning coverage performances of some domestic mobile robots

23、 are measured, analyzed and modeled. Results obtained in a reduced scenario show that floor-cleaning coverage is complete in all cases if the path-planning exploration algorithm has some random dependence. Additionally, the evolution of the area cleaned by the mobile robot expressed in a distance do

24、main has an exponential shape that can be modeled with a single exponential where the amplitude defines the maximum cleaning-coverage achieved and the time-constant defines the dynamic evolution of the coverage. Both parameters are robot dependent and can be estimated if the area of the room is know

25、n and then floor-cleaning coverage can be predicted and over-cleaning minimized.In tellige nt task pla nning and action select ion of a mobile robot in a multi-age ntsystem through a fuzzy n eural n etwork approachThis paper proposes an intelligent task planning and action selection mechanism for a

26、mobile robot in arobot soccer system through a fuzzy neural network approach. The proposed fuzzy neural network system is developed through the two dimensional fuzzification of the soccer field. A five layer fuzzy neural network system is trained through error back propagation learning algorithm to

27、impart a strategy based action selection. The action selection depends on the field configuration, and the emergence of a particular field configuration results from the game dynamics. Strategy of the robot changes when the configuration of the objects in the field changes. The proposed fuzzy neural

28、 network structure is flexible to accommodate all possible filed configurations. Simulation results indicate that the proposed approach is simple and has the capability in coordinating the multi-agent system through selection of sensible actions.In teractive teachi ng of task-orie nted robot graspsT

29、his paper focuses on the problem of grasp stability and grasp quality analysis. An elegant way toevaluate the stability of a grasp is to model its wrench space. However, classical grasp quality measures suffer from several disadvantages, the main drawback being that they are not task related. Indeed

30、, constructive approaches for approximating the wrench space including also task information have been rarely considered. This work presents an effective method for task-oriented grasp quality evaluation based on a novel grasp quality measure. We address the general case of multifingered grasps with

31、 point contacts with friction.The proposed approach is based on the concept of programming by demonstration and interactive teaching, wherein an expert user provides in a teaching phase a set of exemplar grasps appropriate for the task. Following this phase, a representation of task-related grasps i

32、s built. During task planning and execution, a grasp could be either submitted interactively for evaluation by a non-expert user or synthesized by an automatic planning system. Grasp quality is then assessed based on the proposed measure, which takes into account grasp stability along with its suita

33、bility for the task. To enable real-time evaluation of grasps, a fast algorithm for computing an approximation of the quality measure is also proposed. Finally, a local grasp optimization technique is described which can amend uncertainties arising in supplied grasps by non-expert users or assist in

34、 planning more valuable grasps in the neighborhood of candidate ones.The paper reports experiments performed in virtual reality with both an anthropomorphic virtual hand and a three-fingered robot hand. These experiments suggest the effectiveness and task relevance of the proposed grasp quality meas

35、ure.Huma n -robot com muni cati on for collaborative decisi on maki ng A probabilisticapproachHumans and robots need to exchange information if the objective is to achievea task collaboratively. Two questions are considered in this paper: what and when to communicate. To answer these questions, we d

36、eveloped a human-robot communication framework which makes use ofcommon probabilistic robotics representations. The data stored in the representation determines what to communicate, and probabilistic inference mechanisms determine when to communicate. One application domain of the framework is colla

37、borative human -robot decision making: robots use decision theory toselect actions based on perceptual information gathered from their sensors and human operators. In this paper, operators are regarded as remotely located, valuable information sources which need to be managed carefully. Robots decid

38、e when to query operators using Value-Of-Information theory,i.e. humans are only queried if the expected benefit of their observation exceeds the cost of obtaining it.This can be seen as a mechanism for adjustable autonomy whereby adjustments are triggered at run-time based on the uncertainty in the robots beliefs related to their task.