Safe and optimal navigation for autonomous multi-rotor aerial vehicle in a dynamic known environment by a decomposition-coordination method

In this paper, we present a new solution for the Autonomous navigation problem, using a Decomposition-Coordination Method (DCM) 1. The main purpose of this work is to compute an optimal and safe path for the multi-rotor Unmanned Aerial Vehicle (UAV) in a dynamic environment, moving from an initial location to the desired state. We assume that the flight environment is totally known to a supervisory unit, and the positions and trajectories of dynamic obstacles could be known in real-time, thus to perform in such environment a high reactivity is required as well as good connectivity with the supervisory unit that provides the safe path, each time one obstacle or more are detected on the road, so that the UAV could autonomously diverts from the unsafe path to the new safe one, and avoid the potential collisions. First and foremost, we choose a generalized nonlinear model for the multi-rotors in view of the rotational and translational dynamics of the UAV. We then associate that model with the objective functions. After that, we proceed to the resolution of the multi-objective optimization problem using our approach of decomposition-coordination. The principle of this method consists in decomposing the system into several smaller subsystems to simplify the treatment. Then we achieve the coordination afterward using Lagrange multipliers. To prove the convergence and stability of our method we make use of a Lyapunov function chosen particularly for this system. In the last section we present the simulation results, to confirm the reliability of our method.     

Planet Braitenberg: Experiments in virtual psychology

Braitenberg vehicles are simple robotic platforms, equipped with rudimentary sensor and motor components. Such vehicles have typically featured as part of thought experiments that are intended to show how complex behaviours are apt to emerge from the interaction of inner control mechanisms with aspects of bodily structure and features of the wider (extra-agential) environment. The present paper describes a framework for creating Braitenberg-like vehicles, which is built on top of a widely used and freely available game engine, namely, the Unity game engine. The framework can be used to study the behaviour of virtual vehicles within a multiplicity of virtual environments. All aspects of the vehicle’s design, as well as the wider virtual environment in which the vehicle is situated, can be modified during the design phase, as well as at runtime. The result is a general-purpose simulation capability that is intended to provide the foundation for studies in so-called computational situated cognition—a field of study whose primary objective is to support the computational modelling of cognitive processes associated with the physically-embodied, environmentally-embedded, and materially-extended mind.     

Kinaesthetic imagery ability moderates the effect of an AO+MI intervention on golf putt performance: A pilot study

BackgroundPrevious research has established that motor imagery (MI) and action observation (AO) independently enhance the performance and learning of motor skills. Recent studies have demonstrated that combining AO and MI (AO + MI) elicits increased activity in motor regions of the brain and enhances performance more than either AO or MI alone. Kinesthetic imagery (KI) ability refers to the ease with which one can sense their own body and imagine how a movement feels during a task (Malouin et al., 2007). KI ability may be of particular importance when engaging with AO + MI as the provision of an external visual stimulus through AO renders the visual component of MI redundant.ObjectiveThe current study aims to add to the emerging body of behavioural evidence demonstrating the performance benefits of AO + MI by exploring the effect of an AO + MI intervention on golf putting performance, as well as exploring the role that KI ability represents in AO + MI effectiveness.MethodRight-handed male golfers (N = 44) of varying skill level performed twenty 15-foot putts before and after a 3.5 min AO + MI intervention (AO + MI group; mean handicap = 7.5, SD = 4.3) or a similarly timed passive reading task (Control group; mean handicap = 11.5, SD = 5.4). Using the MIQ-3 questionnaire, participants in both experimental groups were classified according to kinesthetic imagery ability where: a mean score ≥6 were classified as good imagers. Performance accuracy was measured using mean radial error (MRE), precision was quantified via bivariate error (BVE) and putter kinematics were recorded by SAM Puttlab.ResultsResults from a series of ANCOVAs indicate that good kinesthetic imagers who received the AO + MI intervention were significantly more precise (BVRE) on the putting task than good kinesthetic imagers in the Control group (p = 0.041, d = 0.678). Good kinesthetic imagers in the intervention group also significantly outperformed good kinesthetic imagers in the control group on a measure of speed control (SD of error scores along the axis of progression) in golf putting (p = 0.041).ConclusionsOur results suggest that the presence of AO with MI increases the relevance of kinesthetic cues, that good kinesthetic imagers are able to utilise for subsequent performance benefits during the putting task. We discuss the increased importance of kinesthetic awareness/feel following the intervention as an explanation for such improvements in performance.     

具身认知视角的饮食消费行为——基于心理模拟“具身”方式

随着具身认知理论的发展, 基于心理模拟“具身”方式的饮食消费行为研究得到了一些新颖、有趣的研究结果, 为过食与肥胖、食品营销等问题的解决提供了新视角。心理模拟既能促进进食也能抑制进食; 心理模拟容易性因素与动机性因素是影响心理模拟程度的两大类主要前因变量; 未来需要进一步探索心理模拟的容易性因素与动机性因素、心理模拟提高消费欲望与产生腻厌反应的边界条件, 以及利用心理模拟探讨肥胖高危人群——高奖赏敏感性个体过食的深层次内在机制等。     

概化理论方差分量及其变异量估计:跨分布的模拟研究

为考察概化理论中方差分量及其变异量估计的准确性,采用模拟研究的方法,探究Traditional法、Jackknife法、Bootstrap法和MCMC法在p×i×h和p×(i:h)2种双侧面设计和正态、二项、多项、偏态分布4种数据类型下的表现。结果显示:(1)4种方法均能准确估计方差分量;(2)估计方差分量的标准误时,若数据正态分布,Traditional法最优,非正态分布时Bootstrap法最优;(3)估计方差分量的90%置信区间时,Bootstrap法在不同分布的数据下表现稳定,但容易受到侧面水平数的影响。综合来说,若数据呈正态分布,建议选用Traditional法; 若数据呈非正态分布,建议选用Bootstrap法。     

主人公的动机水平对句子理解中心理模拟的影响

通过两个实验, 考察了主人公的动机水平对句子理解中读者的心理模拟的影响。实验1采用移动窗口技术, 记录读者阅读句子中目的地词语的时间; 实验2采用视觉情景眼动范式, 主试播放描述运动的句子, 同时呈现相应的情境图片, 记录读者扫描图片中主人公、路径和目的地的时间。实验结果表明：(1)主人公的动机水平影响读者对目的地词语的阅读时间, 主人公的动机水平越高, 读者的阅读时间就越短; (2)读者对情景图片的扫描受主人公的动机水平影响, 主人公的动机水平越高, 读者对路径区域的扫描时间就越短, 对目的地区域的扫描时间就越长。两个实验均表明, 在句子的实时加工中, 读者可以通过再入情境, 遵循先内后外的顺序, 先模拟主人公的动机水平, 继而模拟主人公的动作, 从而影响对句子的注视和理解。研究结果支持语言加工的具身认知观。     

Simulating biological and non-biological motion

It is widely accepted that the brain processes biological and non-biological movements in distinct neural circuits. Biological motion, in contrast to non-biological motion, refers to active movements of living beings. Aim of our experiment was to investigate the mechanisms underlying mental simulation of these two movement types. Subjects had to either simulate mentally or to overtly reproduce previously executed or observed movements. Healthy subjects showed a very high timing precision when simulating biological and a strong distortion when simulating non-biological movements. Schizophrenic subjects, however, showed the opposite. Since overt reproduction was precise in any case, this double dissociation shows that processes underlying mental simulation of biological and non-biological movements are separate from each other and from perceptual and motor-control processes.     

Bootstrapping cognition from behavior-a computerized thought experiment

We show that simple perceptual competences can emerge from an internal simulation of action effects and are thus grounded in behavior. A simulated agent learns to distinguish between dead ends and corridors without the necessity to represent these concepts in the sensory domain. Initially, the agent is only endowed with a simple value system and the means to extract low-level features from an image. In the interaction with the environment, it acquires a visuo-tactile forward model that allows the agent to predict how the visual input is changing under its movements, and whether movements will lead to a collision. From short-term predictions based on the forward model, the agent learns an inverse model. The inverse model in turn produces suggestions about which actions should be simulated in long-term predictions, and long-term predictions eventually give rise to the perceptual ability.     

Computer simulation through an error-statistical lens

After showing how Deborah Mayo’s error-statistical philosophy of science might be applied to address important questions about the evidential status of computer simulation results, I argue that an error-statistical perspective offers an interesting new way of thinking about computer simulation models and has the potential to significantly improve the practice of simulation model evaluation. Though intended primarily as a contribution to the epistemology of simulation, the analysis also serves to fill in details of Mayo’s epistemology of experiment.     

因子分析元分析的三阶段整合模型

因子分析元分析(meta-analysis of factor analyses, MAFA)整合了因子分析和元分析两种方法学传统。开展MAFA方法学研究可结束过去几十年MAFA研究缺乏根据的状况, 服务心理学等领域内的知识生产。三阶段整合模型认为MAFA包括数据准备、数据合成和数据分析三个主要阶段。模型及数据合成技术的有效性将用心理测量学方法, 包括蒙特卡洛模拟研究进行检验。研究结果将阐明正确运用MAFA的一般规则、操作步骤和注意事项, 进而增进我们对MAFA的认识, 丰富应用心理等领域的方法学体系, 为MAFA方法的推广应用奠定基础。