Gait Planning Of Quadruped Robot Based On Third-Order Spline Interpolation
This paper presented a brief description for the gait planning of quadruped robot named Aibo ERS-7 which is a standard platform in the RoboCup 4-legged league. We approach a spline shaped locus to reduce the dimension of the parameter optimizing space and solve the problem of the significant bias between the planned locus and the real one. The result shows that the spline shaped locus is effective in finding the optimized locus shape in a short time. Finally, the robot achieves a gait faster than any previously known learned gait for Aibo

title: Humanoid Robot Gait Generation Based on Limit Cycle Stability
abstract: This paper presents the gait generation and mechanical design of a humanoid robot based on a limit cycle walking method-Virtual Slope Control. This method is inspired by Passive Dynamic Walking. By shortening the swing leg, the robot walking on level ground can be considered as on a virtual slope. Parallel double crank mechanisms and elastic feet are introduced to the 5 DoF robot leg, to make the heelstrike of the swing leg equivalent to the point-foot collision used in Virtual Slope Control. In practical walking, the gait is generated by connecting the two key frames in the sagittal and lateral plane with sinusoids. With the addition of leg rotational movement, the robot achieves a fast forward walking of 2.0leg/s and accomplishes omnidirectional walking favorably.

title: Effect of energy feedbacks on Virtual Slope Walking: I. Complementary Energy Feedback
abstract: This paper presents our study over the effect of Complementary Energy Feedback on Virtual Slope Walking, while Virtual Slope Walking is our new biped gait generation method inspired by Passive Dynamic Walking. The energy feedback strength is defined and the walking is modeled as a step-to-step function. The Jacobi Matrix eigenvalues of the function are calculated together with the basin of attraction. From the analysis, we find the characteristic of Complementary Energy Feedback is being effective on a fast gait but weak on a slow one. By making use of the Complementary Energy Feedback in walking experiment, our robot achieves speed change from 1.5leg/s to 4.1leg/s.

title: An Adaptive Selection of Motion for Online Hand-Eye Calibration
abstract: As the robot makes unplanned movement, online hand-eye calibration determines the relative pose between the robot gripper/end-effector and the sensors mounted on it. With noisy measurements, hand-eye calibration is sensitive to small rotations in real applications. Moreover, degenerate cases such as pure translations have no effect in hand-eye calibration. This paper proposes an adaptive motion selection algorithm for online hand-eye calibration, which can adaptively set the thresholds of motion selection according to the characteristics of the unplanned motion sequence. It is achieved by using polynomial-regression to predict the relationship between RMS of calibration error and thresholds. Thus, this procedure leads to an adaptive method of motion selection. It can adapt itself to online hand-eye calibration in various applications. Experiments using simulated data are conducted and present good results. Experiments using real scenes also show that the method is promising.

title: Personalized QoS Prediction forWeb Services via Collaborative Filtering
abstract: Many researchers propose that, not only functional but also non-functional properties, also known as quality of service (QoS), should be taken into consideration when consumers select services. Consumers need to make prediction on quality of unused web services before selecting. Usually, this prediction is based on other consumers' experiences. Being aware of different QoS experiences of consumers, this paper proposes a collaborative filtering based approach to making similarity mining and prediction from consumers' experiences. Experimental results demonstrate that this approach can make significant improvement on the effectiveness of QoS prediction for web services.

title: Dynamic Negotiation for Real-Time Manufacturing Execution
abstract: This paper presents a dynamic negotiation framework for real-time execution in self-organised manufacturing environments. The negotiation strategies in this framework bridge the gap between distributed negotiation of self-interested agents and cooperative negotiation among agent groups. In particular, the proposed framework is based on the model of Performance and Cost for Manufacturing Execution (PCME). By forming the dynamic organisation called agent consortium, individual agents negotiate over the PCME in order to optimise the resource allocation under time constraints and uncertainty of job execution, and resolve the conflicts to fulfil the goal of the overall system. The ultimate goal of the framework is to reduce the negotiation time, make effective use of resources, adapt to the changes in execution and increase the throughput of the entire system. Experimental work based on PCME has been carried out to demonstrate the high performance of this approach despite unanticipated and dynamic changes in the manufacturing execution environments.

title: Evolutionary Algorithm Based on Overlapped Gene Expression
abstract: Inspired by the overlap gene expression in biological study, this paper proposes a novel evolutionary algorithm-EAOGE i.e. Evolutionary Algorithm based on Overlapped Gene Expression. Different from existing works, EAOGE suggests a new expression structure of genes with probabilities of overlapped expression for some segments. The main contributions are: (1) Proposing a novel model and an algorithm of gene expression while borrowing some ideas from artificial immunity algorithm; (2) Analyzing the expressing space and encode characteristic of the new model; (3) The extensive experiments in function finding shows that new model is 2.8~9.7 times faster than usual GEP method, and in higher-degree polynomial function finding, the success rate of EAOGE is over 10 times than usual GEP.

title: Extraction and mining of an academic social network
abstract: This paper addresses several key issues in extraction and mining of an academic social network: 1) extraction of a researcher social network from the existing Web; 2) integration of the publications from existing digital libraries; 3) expertise search on a given topic; and 4) association search between researchers. We developed a social network system, called ArnetMiner, based on proposed methods to the above problems. In total, 448,470 researcher profiles and 981,599 publications were extracted/integrated after the system having been in operation for two years. The paper describes the architecture and main features of the system. It also briefly presents the experimental results of the proposed methods.