Finite-time coordination in multiagent systems using sliding mode control approach

Finite-time stability in dynamical systems theory involves systems whose trajectories converge to an equilibrium state in finite time. In this paper, we use the notion of finite-time stability to apply it to the problem of coordinated motion in multiagent systems. Specifically, we consider a group of agents described by fully actuated Euler–Lagrange dynamics along with a leader agent with an objective to reach and maintain a desired formation characterized by steady-state distances between the neighboring agents in finite time. We use graph theoretic notions to characterize communication topology in the network determined by the information flow directions and captured by the graph Laplacian matrix. Furthermore, using sliding mode control approach, we design decentralized control inputs for individual agents that use only data from the neighboring agents which directly communicate their state information to the current agent in order to drive the current agent to the desired steady state. Sliding mode control is known to drive the system states to the sliding surface in finite time. The key feature of our approach is in the design of non-smooth sliding surfaces such that, while on the sliding surface, the error states converge to the origin in finite time, thus ensuring finite-time coordination among the agents in the network. In addition, we discuss the case of switching communication topologies in multiagent systems. Finally, we show the efficacy of our theoretical results using an example of a multiagent system involving planar double integrator agents.     

A 3D analysis of the joint torques developed during driver's ingress–egress motion

Providing an easy ingress–egress (I/E) movement remains a challenge for car designers. I/E has been largely studied in kinematics, but not in dynamics. This study proposes: (1) to evaluate and describe the motor torques developed in the lower limbs and lumbar joints during I/E motions and (2) to analyse the influence of the car geometry and subject anthropometry. An experiment was performed to observe 15 subjects of three anthropometrical groups getting in and out of a car mock-up simulating three different vehicle configurations. Motor torques were extracted using an inverse dynamics analysis. Both ingress and egress motions were primarily characterised by large torques. Overall, the taller a subject and the lower the seat of the vehicle were, the larger the peak torques were. Moreover, peak torques were higher for egress than ingress. These results are discussed in regard to the current knowledge on I/E ergonomics.     

Alcohol consumption detection through behavioural analysis using intelligent systems

We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC value of a subject, we perform a behaviour analysis of this subject using intelligent systems. We monitor the user’s actions in an ordinary task and label those data to various measured BAC values. The obtained data-set is then used to train learning systems to detect alcoholic consumption and perform BAC estimation. We obtain good results on a mono-user base, and lower results with multiple users. We improve the results by combining multiple classifiers and regression algorithms.     

用于虚拟现实的360度视频编码技术新进展*

随着虚拟现实技术不断发展,360度视频编码开始成为研究热点。应用于虚拟现实的360度视频与传统的视频相比分辨率更高,编码数据量更大,在实际应用中面临传输带宽有限的瓶颈,编码效率问题有待解决。归纳分析了国际标准组织联合视频研究组（joint video exploration team, JVET）正在制定的360度视频编码投影变换技术及其编码优化方法,综合对比了各变换技术的编码性能。根据当前最新研究成果,对下一步研究需要解决的问题进行了探讨总结,给出未来的研究方向和思路。     

弯道岸坡上粗细泥沙统一起动流速公式

该文基于概率论与泥沙起动基本理论,考虑了起动概率、相对暴露度与细颗粒泥沙间黏结力和附加下压力对泥沙起动的影响,采用滑动起动模型,从理论上推导出了适用于弯道岸坡上粗、细泥沙颗粒起动的统一流速公式,完善了已有研究成果对泥沙起动概率考虑的不足。公式综合了弯道岸坡、顺直岸坡、正负坡及平坡等条件下粗细泥沙颗粒起动流速计算,可简化为各简单条件下泥沙起动流速公式。通过各简单条件下泥沙起动流速实测资料验证,该文公式与实测数据符合良好。     

Beauty is more than screen deep: Improving the web survey respondent experience through socially-present and aesthetically-pleasing user interfaces

Web surveys are rapidly becoming standard issue in many researchers’ toolkits; however, measurement error has been shown to affect web surveys to a greater extent than paper-and-pencil surveys (Couper, 2000, Manfreda and Vehovar, 2002). Principles of aesthetic design and social presence have been applied to web surveys to reduce the prevalence of such error with promising results, which were further investigated in this research. A sample of 181 first-year psychology undergraduate students participated in this study. Participants were randomly allocated to view one of eight web survey interfaces, which varied by aesthetic quality and social presence. Exploratory structural equation modeling using the partial least squares method revealed that classical aesthetic quality and social presence were both positively related to perceived ease of use of the web survey interface and positive state affect; social presence and perceived ease of use were positively related to trust in the web survey researcher; classical aesthetic quality was negatively related to negative state affect; and, expressive aesthetic quality was negatively related to perceived ease of use and positively related to positive state affect. Interestingly, expressive aesthetic quality was also positively related to negative state affect. These relationships between aesthetic quality and social presence should inform best practice web survey design recommendations, and future empirical work should extend and test the generalizability of these findings.     

Level of interest sensing in spoken dialog using decision-level fusion of acoustic and lexical evidence

Automatic detection of a user's interest in spoken dialog plays an important role in many applications, such as tutoring systems and customer service systems. In this study, we propose a decision-level fusion approach using acoustic and lexical information to accurately sense a user's interest at the utterance level. Our system consists of three parts: acoustic/prosodic model, lexical model, and a model that combines their decisions for the final output. We use two different regression algorithms to complement each other for the acoustic model. For lexical information, in addition to the bag-of-words model, we propose new features including a level-of-interest value for each word, length information using the number of words, estimated speaking rate, silence in the utterance, and similarity with other utterances. We also investigate the effectiveness of using more automatic speech recognition (ASR) hypotheses (n-best lists) to extract lexical features. The outputs from the acoustic and lexical models are combined at the decision level. Our experiments show that combining acoustic evidence with lexical information improves level-of-interest detection performance, even when lexical features are extracted from ASR output with high word error rate.     

Paramedics on the job: Dynamic trunk motion assessment at the workplace

Many paramedics' work accidents are related to physical aspects of the job, and the most affected body part is the low back. This study documents the trunk motion exposure of paramedics on the job. Nine paramedics were observed over 12 shifts (120 h). Trunk postures were recorded with the computer-assisted CUELA measurement system worn on the back like a knapsack. Average duration of an emergency call was 23.5 min. Sagittal trunk flexion of >40° and twisting rotation of >24° were observed in 21% and 17% of time-sampled postures. Medical care on the scene (44% of total time) involved prolonged flexed and twisted postures (∼10 s). The highest extreme sagittal trunk flexion (63°) and twisting rotation (40°) were observed during lifting activities, which lasted 2% of the total time. Paramedics adopted trunk motions that may significantly increase the risk of low back disorders during medical care and patient-handling activities.     

Delay time compensation based on coefficient of restitution for collision hybrid motion simulator

A hybrid motion simulator embeds a hardware experiment in a numerical simulation loop. However, it is often subjected to the inherent problem of an energy increase in the collision of two pieces of hardware in a loop because of the delay time. This paper proposes a delay time compensation method based on contact dynamics model for a collision hybrid motion simulator under delay time and establishes a compensation method for coupled translational and rotational motion. The model developed in this paper describes linear uniform motion of a floating object during the period of the delay time until the force and torque are observed and non-linear motion according to environmental stiffness after the initial delay time period in contact. By using the above model, compensation parameters are designed based on desired coefficient of restitution with iterative calculation. The proposed method achieves accurate delay time compensation and simultaneously realizes a variable desired coefficient of restitution over a wide range of frequencies. Furthermore, the compensation method for multi-dimensional motion is established under the assumption that the friction effect is very small. The efficiency of the proposed method is verified through collision experiments for the coupled motion in two dimensions.     

Perception of own and robot engagement in human–robot interactions and their dependence on robotics knowledge

Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human’s own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot’s engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human–robot interactions without affecting the impact of the type of signal sent by the robot.