Third Conference on Artificial Intelligence for Space Applications, part 2

Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed

Adaptive Airborne Separation to Enable UAM Autonomy in Mixed Airspace

The excitement and promise generated by Urban Air Mobility (UAM) concepts have inspired both new entrants and large aerospace companies throughout the world to invest hundreds of millions in research and development of air vehicles, both piloted and unpiloted, to fulfill these dreams. The management and separation of all these new aircraft have received much less attention, however, and even though NASAs lead is advancing some promising concepts for Unmanned Aircraft Systems (UAS) Traffic Management (UTM), most operations today are limited to line of sight with the vehicle, airspace reservation and geofencing of individual flights. Various schemes have been proposed to control this new traffic, some modeled after conventional air traffic control and some proposing fully automatic management, either from a ground-based entity or carried out on board among the vehicles themselves. Previous work has examined vehicle-based traffic management in the very low altitude airspace within a metroplex called UTM airspace in which piloted traffic is rare. A management scheme was proposed in that work that takes advantage of the homogeneous nature of the traffic operating in UTM airspace. This paper expands that concept to include a traffic management plan usable at all altitudes desired for electric Vertical Takeoff and Landing urban and short-distance, inter-city transportation. The interactions with piloted aircraft operating under both visual and instrument flight rules are analyzed, and the role of Air Traffic Control services in the postulated mixed traffic environment is covered. Separation values that adapt to each type of traffic encounter are proposed, and the relationship between required airborne surveillance range and closure speed is given. Finally, realistic scenarios are presented illustrating how this concept can reliably handle the density and traffic mix that fully implemented and successful UAM operations would entail

Autonomous flight and remote site landing guidance research for helicopters

Automated low-altitude flight and landing in remote areas within a civilian environment are investigated, where initial cost, ongoing maintenance costs, and system productivity are important considerations. An approach has been taken which has: (1) utilized those technologies developed for military applications which are directly transferable to a civilian mission; (2) exploited and developed technology areas where new methods or concepts are required; and (3) undertaken research with the potential to lead to innovative methods or concepts required to achieve a manual and fully automatic remote area low-altitude and landing capability. The project has resulted in a definition of system operational concept that includes a sensor subsystem, a sensor fusion/feature extraction capability, and a guidance and control law concept. These subsystem concepts have been developed to sufficient depth to enable further exploration within the NASA simulation environment, and to support programs leading to the flight test

Algoritmo de planificación de movimiento para un robot móvil con un sistema de visión artificial inteligente

Este estudio está dedicado a los desafíos de la planificación del movimiento para robots móviles con sistemas inteligentes de visión artificial. La planificación del movimiento para robots móviles en un entorno con obstáculos es un problema con el que lidiar al crear robots adecuados para operar en condiciones del mundo real. Las soluciones que se encuentran en la actualidad son predominantemente privadas y altamente especializadas, lo que impide juzgar qué tan exitosas son para resolver el problema de la planificación eficaz del movimiento. Ya existen soluciones con un campo de aplicación estrecho y ya se están desarrollando durante mucho tiempo, sin embargo, aún no se han observado avances importantes. Solo se puede observar una mejora sistemática en las características de tales sistemas. El propósito de este estudio: desarrollar e investigar un algoritmo de planificación de movimiento para un robot móvil con un sistema de visión artificial inteligente. El tema de investigación de este artículo es un algoritmo de planificación de movimiento para un robot móvil con un sistema de visión artificial inteligente. Este estudio proporciona una revisión de robots móviles nacionales y extranjeros que resuelven el problema de planificación de movimiento en un entorno conocido con obstáculos desconocidos. Se consideran los siguientes métodos de navegación para robots móviles: local, global, individual. En el transcurso del trabajo e investigación se ha construido un prototipo de robot móvil, capaz de reconocer obstáculos de formas geométricas regulares, así como planificar y corregir la trayectoria del movimiento. Los objetos del entorno se identifican y clasifican como obstáculos mediante métodos y algoritmos de procesamiento de imágenes digitales. La distancia al obstáculo y el ángulo relativo se calculan mediante métodos de fotogrametría, la calidad de la imagen se mejora mediante la mejora del contraste lineal y el filtrado lineal óptimo utilizando la ecuación de Wiener-Hopf. Se han revisado las herramientas virtuales, relacionadas con las pruebas de algoritmos de movimiento de robots móviles, lo que nos llevó a seleccionar el paquete de software Webots para las pruebas de prototipos. Los resultados de las pruebas nos permitieron sacar las siguientes conclusiones. El robot móvil identificó con éxito el obstáculo, planificó una ruta de acuerdo con el algoritmo de evitación de obstáculos y continuó avanzando hacia el destino. Se han extraído conclusiones con respecto a la investigación concluida

Algoritmo de planificación de movimiento para un robot móvil con un sistema de visión artificial inteligente

This study is devoted to the challenges of motion planning for mobile robots with smart machine vision systems. Motion planning for mobile robots in the environment with obstacles is a problem to deal with when creating robots suitable for operation in real-world conditions. The solutions found today are predominantly private, and are highly specialized, which prevents judging of how successful they are in solving the problem of effective motion planning. Solutions with a narrow application field already exist and are being already developed for a long time, however, no major breakthrough has been observed yet. Only a systematic improvement in the characteristics of such systems can be noted. The purpose of this study: develop and investigate a motion planning algorithm for a mobile robot with a smart machine vision system. The research subject for this article is a motion planning algorithm for a mobile robot with a smart machine vision system. This study provides a review of domestic and foreign mobile robots that solve the motion planning problem in a known environment with unknown obstacles. The following navigation methods are considered for mobile robots: local, global, individual. In the course of work and research, a mobile robot prototype has been built, capable of recognizing obstacles of regular geometric shapes, as well as plan and correct the movement path. Environment objects are identified and classified as obstacles by means of digital image processing methods and algorithms. Distance to the obstacle and relative angle are calculated by photogrammetry methods, image quality is improved by linear contrast enhancement and optimal linear filtering using the Wiener-Hopf equation. Virtual tools, related to mobile robot motion algorithm testing, have been reviewed, which led us to selecting Webots software package for prototype testing. Testing results allowed us to make the following conclusions. The mobile robot has successfully identified the obstacle, planned a path in accordance with the obstacle avoidance algorithm, and continued moving to the destination. Conclusions have been drawn regarding the concluded research.Este estudio está dedicado a los desafíos de la planificación del movimiento para robots móviles con sistemas inteligentes de visión artificial. La planificación del movimiento para robots móviles en un entorno con obstáculos es un problema con el que lidiar al crear robots adecuados para operar en condiciones del mundo real. Las soluciones que se encuentran en la actualidad son predominantemente privadas y altamente especializadas, lo que impide juzgar qué tan exitosas son para resolver el problema de la planificación eficaz del movimiento. Ya existen soluciones con un campo de aplicación estrecho y ya se están desarrollando durante mucho tiempo, sin embargo, aún no se han observado avances importantes. Solo se puede observar una mejora sistemática en las características de tales sistemas. El propósito de este estudio: desarrollar e investigar un algoritmo de planificación de movimiento para un robot móvil con un sistema de visión artificial inteligente. El tema de investigación de este artículo es un algoritmo de planificación de movimiento para un robot móvil con un sistema de visión artificial inteligente. Este estudio proporciona una revisión de robots móviles nacionales y extranjeros que resuelven el problema de planificación de movimiento en un entorno conocido con obstáculos desconocidos. Se consideran los siguientes métodos de navegación para robots móviles: local, global, individual. En el transcurso del trabajo e investigación se ha construido un prototipo de robot móvil, capaz de reconocer obstáculos de formas geométricas regulares, así como planificar y corregir la trayectoria del movimiento. Los objetos del entorno se identifican y clasifican como obstáculos mediante métodos y algoritmos de procesamiento de imágenes digitales. La distancia al obstáculo y el ángulo relativo se calculan mediante métodos de fotogrametría, la calidad de la imagen se mejora mediante la mejora del contraste lineal y el filtrado lineal óptimo utilizando la ecuación de Wiener-Hopf. Se han revisado las herramientas virtuales, relacionadas con las pruebas de algoritmos de movimiento de robots móviles, lo que nos llevó a seleccionar el paquete de software Webots para las pruebas de prototipos. Los resultados de las pruebas nos permitieron sacar las siguientes conclusiones. El robot móvil identificó con éxito el obstáculo, planificó una ruta de acuerdo con el algoritmo de evitación de obstáculos y continuó avanzando hacia el destino. Se han extraído conclusiones con respecto a la investigación concluida

Research status of agricultural robot technology

According to the different agricultural production uses, agricultural robots were classified, mainly including agricultural information collection robots, pruning robots, grafting robots, transplanting robots, spraying robots and picking robots. The research status of mainstream agricultural robots at home and abroad were introduced, and their working principles and characteristics were expounded. Finally, the problems existing in the key technologies of existing agricultural robots and their future development directions were put forward

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Safe, Remote-Access Swarm Robotics Research on the Robotarium

This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference

Localization and 2D Mapping Using Low-Cost Lidar

Autonomous vehicles are expected to make a profound change in auto industry. An autonomous vehicle is a vehicle that is able to sense its surroundings and travel with little or no human intervention. The four key capabilities of autonomous vehicles are a comprehensive understanding of sensor data, knowledge of their positions in the world, building the map of unknown environment, as well as following the planed route and collision avoidance. This thesis is aimed at building a low-cost autonomous vehicle prototype that is capable of localization and 2D mapping simultaneously. In addition, the prototype should be able to detect obstacles and avoid collision. In this thesis, a Redbot is utilized as a moving vehicle to evaluate collision avoidance functionality. A mechnical bumper in front of the Redbot is used to detect obstacles, and a remote user can send appropriate commands to control the Redbot via Zigbee network, then Redbot acts accordingly, including driving straightly, changing direction to right or left, and stop. Redbot are also used to carry the lidar scanner which consists of Lidar Lite V3 and a servo motor. Lidar data are sent back to a Laptop running ROS via Zigbee network. In ROS, Hector SLAM metapackage is adopted to process the lidar data, and realize the functionality of simultaneous localization and 2D mapping. After implementing the autonomous vehicle prototype, a series of tests are con- ducted to evaluate the functionality of localization, 2D mapping, obstacle detection, and collision avoidance. The results demonstrated that the prototype is capable of building usable 2D maps of unknown environment, simultaneous localization, obstacle detection and collision avoidance in time. Due to the limited scan range of the low-cost lidar scanner, boundary missing problem can happen. This limitation can be solved through the use of a lidar scanner with larger scan range

SLAM research for port AGV based on 2D LIDAR

With the increase in international trade, the transshipment of goods at international container ports is very busy. The AGV (Automated Guided Vehicle) has been used as a new generation of automated container horizontal transport equipment. The AGV is an automated unmanned vehicle that can work 24 hours a day, increasing productivity and reducing labor costs compared to using container trucks. The ability to obtain information about the surrounding environment is a prerequisite for the AGV to automatically complete tasks in the port area. At present, the method of AGV based on RFID tag positioning and navigation has a problem of excessive cost. This dissertation has carried out a research on applying light detection and ranging (LIDAR) simultaneous localization and mapping (SLAM) technology to port AGV. In this master's thesis, a mobile test platform based on a laser range finder is developed to scan 360-degree environmental information (distance and angle) centered on the LIDAR and upload the information to a real-time database to generate surrounding environmental maps, and the obstacle avoidance strategy was developed based on the acquired information. The effectiveness of the platform was verified by the experiments from multiple scenarios. Then based on the first platform, another experimental platform with encoder and IMU sensor was developed. In this platform, the functionality of SLAM is enabled by the GMapping algorithm and the installation of the encoder and IMU sensor. Based on the established environment SLAM map, the path planning and obstacle avoidance functions of the platform were realized.Com o aumento do comércio internacional, o transbordo de mercadorias em portos internacionais de contentores é muito movimentado. O AGV (“Automated Guided Vehicle”) foi usado como uma nova geração de equipamentos para transporte horizontal de contentores de forma automatizada. O AGV é um veículo não tripulado automatizado que pode funcionar 24 horas por dia, aumentando a produtividade e reduzindo os custos de mão-de-obra em comparação com o uso de camiões porta-contentores. A capacidade de obter informações sobre o ambiente circundante é um pré-requisito para o AGV concluir automaticamente tarefas na área portuária. Atualmente, o método de AGV baseado no posicionamento e navegação de etiquetas RFID apresenta um problema de custo excessivo. Nesta dissertação foi realizada uma pesquisa sobre a aplicação da tecnologia LIDAR de localização e mapeamento simultâneo (SLAM) num AGV. Uma plataforma de teste móvel baseada num telémetro a laser é desenvolvida para examinar o ambiente em redor em 360 graus (distância e ângulo), centrado no LIDAR, e fazer upload da informação para uma base de dados em tempo real para gerar um mapa do ambiente em redor. Uma estratégia de prevenção de obstáculos foi também desenvolvida com base nas informações adquiridas. A eficácia da plataforma foi verificada através da realização de testes com vários cenários e obstáculos. Por fim, com base na primeira plataforma, uma outra plataforma experimental com codificador e sensor IMU foi também desenvolvida. Nesta plataforma, a funcionalidade do SLAM é ativada pelo algoritmo GMapping e pela instalação do codificador e do sensor IMU. Com base no estabelecimento do ambiente circundante SLAM, foram realizadas as funções de planeamento de trajetória e prevenção de obstáculos pela plataforma