Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

On Formation of Anthrasemiquinone in the Conditions of Wood Alkaline Pulping

Electron spin resonance (ESR) and electronic absorbance spectral experiments demonstrate that reversible temperature variation of anion-radica1 concentration in the system anthraqui; none (AQ) - anthrasemiquinone (AS) - anthrahydroquinone (AHQ) in aqueous alka1i is a property of that system and not of the more complicated catalyst-wood system. Lignin model compounds present in low concentrations have no influence on this variation. A raise of radical concentration is accompanied by a change of the solution colour from red into yellow. In pulping conditions AQ can be reduced either by the hydrocarbon or by the lignin component of wood, probably also by numerous organic compounds and even by the alka1i itself. As a result of this process, an AQ-AS-AHQ system is being formed

A Data-Efficient Approach for Long-Term Human Motion Prediction Using Maps of Dynamics

Human motion prediction is essential for the safe and smooth operation of mobile service robots and intelligent vehicles around people. Commonly used neural network-based approaches often require large amounts of complete trajectories to represent motion dynamics in complex semantically-rich spaces. This requirement may complicate deployment of physical systems in new environments, especially when the data is being collected online from onboard sensors. In this paper we explore a data-efficient alternative using maps of dynamics (MoD) to represent place-dependent multi-modal spatial motion patterns, learned from prior observations. Our approach can perform efficient human motion prediction in the long-term perspective of up to 60 seconds. We quantitatively evaluate its accuracy with limited amount of training data in comparison to an LSTM-based baseline, and qualitatively show that the predicted trajectories reflect the natural semantic properties of the environment, e.g. the locations of short- and long-term goals, navigation in narrow passages, around obstacles, etc.Comment: in 5th LHMP Workshop held in conjunction with 40th IEEE International Conference on Robotics and Automation (ICRA), 29/05 - 02/06 2023, Londo

Neuromodeling in horticulture and viticulture

The article considers the possibilities of using the artificial intelligence in horticulture and viticulture. At present, the artificial intelligence technologies are actively used in agriculture, which make it possible to effectively determine crop yields, automate the cropping and storage of agricultural produce, determine the condition of the soil, the composition and effective use of fertilizers, identify plant diseases and bring weeds under control using recognition methods. The use of the artificial intelligence methods in horticulture and viticulture has its own specific features: firstly, robotic complexes for harvesting cherries, apricots, apples, peaches and grapes; and secondly, the identification of fruit diseases by means photo recognition using neural networks’ machine learning

CLiFF-LHMP: Using Spatial Dynamics Patterns for Long-Term Human Motion Prediction

Human motion prediction is important for mobile service robots and intelligent vehicles to operate safely and smoothly around people. The more accurate predictions are, particularly over extended periods of time, the better a system can, e.g., assess collision risks and plan ahead. In this paper, we propose to exploit maps of dynamics (MoDs, a class of general representations of place-dependent spatial motion patterns, learned from prior observations) for long-term human motion prediction (LHMP). We present a new MoD-informed human motion prediction approach, named CLiFF-LHMP, which is data efficient, explainable, and insensitive to errors from an upstream tracking system. Our approach uses CLiFF-map, a specific MoD trained with human motion data recorded in the same environment. We bias a constant velocity prediction with samples from the CLiFF-map to generate multi-modal trajectory predictions. In two public datasets we show that this algorithm outperforms the state of the art for predictions over very extended periods of time, achieving 45% more accurate prediction performance at 50s compared to the baseline.Comment: Accepted to the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS

Wetting Control in the Layered Polymer-silver Thin Film via Femtosecond Laser Microstructuring

Water wetting of a structured multi-layered thin film consisting of bottom silver and top polymer layers microstructured by femtosecond laser pulses was studied. The periodic trenches were ablatively produced on the top polymer layer of the film using 515-nm, 220-fs pulses of an ytterbium-doped fiber laser at different pulse energies and the repetition rate of 20 kHz. The topography of the structured film was observed by means of a JEOL 7001F scanning electron microscope and its water wetting angles were measured by side-view microscopic imaging. The wetting angle on the microstructured surface was 144°, comparing to 83° at the raw unstructured surface of the film

Comportamiento destructivo de una persona en retrospectiva histórica: factores, diagnóstico y prevención

In conditions of the current development of society which is characterized by mounting social, economic and political crises, the problem of destructive behavior of an individual acquires special significance and topicality. The paper presents the results of a theoretical and methodological analysis of this problem in foreign and domestic literature in several areas: analysis of the attitude of society towards destructive behavior in its historical aspect; philosophical and theological approach; sociological and demographic areas in the study of destructive behavior, biological and biochemical; genetic approaches; psychological and socio-psychological aspects in the study of destructive behavior of a person. In view of the analysis of various approaches and areas in the study of destructive behavior, the conclusions have been drawn that destructive behavior is represented as a complex phenomenon, caused by biological factors (genetic predisposition, constitutional features of the body structure, the use of psychoactive substances, etc.), social (economic and social crises ), psychopathological (connection with mental disorders), psychological (especially the system of needs and motives of activity), socio-psychological (the impact of socio-psychological maladaptation and characteristics of the values and meaning sphere of an individual) plans. These factors are interconnected and each of them has its own specific role in the complex of destructive behavior, and therefore it is impossible to obtain a holistic view of the phenomenon under consideration taken separately from the entire system of interconnected components.En las condiciones del desarrollo actual de la sociedad, que se caracteriza por el aumento de las crisis sociales, económicas y políticas, el problema del comportamiento destructivo de un individuo adquiere un significado especial y actualidad. El artículo presenta los resultados de un análisis teórico y metodológico de este problema en la literatura extranjera y nacional en varias áreas: análisis de la actitud de la sociedad hacia el comportamiento destructivo en su aspecto histórico; enfoque filosófico y teológico; áreas sociológicas y demográficas en el estudio del comportamiento destructivo, biológico y bioquímico; enfoques genéticos; Aspectos psicológicos y socio-psicológicos en el estudio del comportamiento destructivo de una persona. En vista del análisis de varios enfoques y áreas en el estudio del comportamiento destructivo, se ha llegado a la conclusión de que el comportamiento destructivo se representa como un fenómeno complejo, causado por factores biológicos (predisposición genética, características constitucionales de la estructura del cuerpo, el uso de sustancias psicoactivas, etc.), sociales (crisis económicas y sociales), psicopatológicas (conexión con trastornos mentales), psicológicas (especialmente el sistema de necesidades y motivos de actividad), sociopsicológicas (el impacto de la mala adaptación sociopsicológica y las características de los valores y la esfera de significado de un individuo) planes. Estos factores están interconectados y cada uno de ellos tiene su propio papel específico en el complejo del comportamiento destructivo y, por lo tanto, es imposible obtener una visión holística del fenómeno en consideración tomado por separado del sistema completo de componentes interconectados