553 research outputs found
Aspects of the Rover Problem
The basic task of a rover is to move about automonously in an unknown environment. A working rover must have the following three subsystems which interact in various ways: 1) locomotion--the ability to move, 2) perception--the ability to determine the three-dimensional structure of the environment, and 3) navigation--the ability to negotiate the environment. This paper will elucidate the nature of the problem in these areas and survey approaches to solving them while paying attention to real-world issues.MIT Artificial Intelligence Laborator
Efficient 3D Segmentation, Registration and Mapping for Mobile Robots
Sometimes simple is better! For certain situations and tasks, simple but robust methods can achieve the same or better results in the same or less time than related sophisticated approaches. In the context of robots operating in real-world environments, key challenges are perceiving objects of interest and obstacles as well as building maps of the environment and localizing therein. The goal of this thesis is to carefully analyze such problem formulations, to deduce valid assumptions and simplifications, and to develop simple solutions that are both robust and fast. All approaches make use of sensors capturing 3D information, such as consumer RGBD cameras. Comparative evaluations show the performance of the developed approaches. For identifying objects and regions of interest in manipulation tasks, a real-time object segmentation pipeline is proposed. It exploits several common assumptions of manipulation tasks such as objects being on horizontal support surfaces (and well separated). It achieves real-time performance by using particularly efficient approximations in the individual processing steps, subsampling the input data where possible, and processing only relevant subsets of the data. The resulting pipeline segments 3D input data with up to 30Hz. In order to obtain complete segmentations of the 3D input data, a second pipeline is proposed that approximates the sampled surface, smooths the underlying data, and segments the smoothed surface into coherent regions belonging to the same geometric primitive. It uses different primitive models and can reliably segment input data into planes, cylinders and spheres. A thorough comparative evaluation shows state-of-the-art performance while computing such segmentations in near real-time. The second part of the thesis addresses the registration of 3D input data, i.e., consistently aligning input captured from different view poses. Several methods are presented for different types of input data. For the particular application of mapping with micro aerial vehicles where the 3D input data is particularly sparse, a pipeline is proposed that uses the same approximate surface reconstruction to exploit the measurement topology and a surface-to-surface registration algorithm that robustly aligns the data. Optimization of the resulting graph of determined view poses then yields globally consistent 3D maps. For sequences of RGBD data this pipeline is extended to include additional subsampling steps and an initial alignment of the data in local windows in the pose graph. In both cases, comparative evaluations show a robust and fast alignment of the input data
Automated 3D model generation for urban environments [online]
Abstract
In this thesis, we present a fast approach to automated
generation of textured 3D city models with both high details at
ground level and complete coverage for birds-eye view.
A ground-based facade model is acquired by driving a vehicle
equipped with two 2D laser scanners and a digital camera under
normal traffic conditions on public roads. One scanner is
mounted horizontally and is used to determine the approximate
component of relative motion along the movement of the
acquisition vehicle via scan matching; the obtained relative
motion estimates are concatenated to form an initial path.
Assuming that features such as buildings are visible from both
ground-based and airborne view, this initial path is globally
corrected by Monte-Carlo Localization techniques using an aerial
photograph or a Digital Surface Model as a global map. The
second scanner is mounted vertically and is used to capture the
3D shape of the building facades. Applying a series of automated
processing steps, a texture-mapped 3D facade model is
reconstructed from the vertical laser scans and the camera
images. In order to obtain an airborne model containing the roof
and terrain shape complementary to the facade model, a Digital
Surface Model is created from airborne laser scans, then
triangulated, and finally texturemapped with aerial imagery.
Finally, the facade model and the airborne model are fused
to one single model usable for both walk- and fly-thrus. The
developed algorithms are evaluated on a large data set acquired
in downtown Berkeley, and the results are shown and discussed
Sistemas automáticos de informação e segurança para apoio na condução de veículos
Doutoramento em Engenharia MecânicaO objeto principal desta tese é o estudo de algoritmos de processamento
e representação automáticos de dados, em particular de informação
obtida por sensores montados a bordo de veículos (2D e
3D), com aplicação em contexto de sistemas de apoio à condução.
O trabalho foca alguns dos problemas que, quer os sistemas de condução
automática (AD), quer os sistemas avançados de apoio à condução
(ADAS), enfrentam hoje em dia. O documento é composto por
duas partes. A primeira descreve o projeto, construção e desenvolvimento
de três protótipos robóticos, incluindo pormenores associados
aos sensores montados a bordo dos robôs, algoritmos e arquitecturas
de software. Estes robôs foram utilizados como plataformas de ensaios
para testar e validar as técnicas propostas. Para além disso, participaram
em várias competições de condução autónoma tendo obtido
muito bons resultados. A segunda parte deste documento apresenta
vários algoritmos empregues na geração de representações intermédias
de dados sensoriais. Estes podem ser utilizados para melhorar
técnicas já existentes de reconhecimento de padrões, deteção ou navegação,
e por este meio contribuir para futuras aplicações no âmbito dos
AD ou ADAS. Dado que os veículos autónomos contêm uma grande
quantidade de sensores de diferentes naturezas, representações intermédias
são particularmente adequadas, pois podem lidar com problemas
relacionados com as diversas naturezas dos dados (2D, 3D, fotométrica,
etc.), com o carácter assíncrono dos dados (multiplos sensores
a enviar dados a diferentes frequências), ou com o alinhamento
dos dados (problemas de calibração, diferentes sensores a disponibilizar
diferentes medições para um mesmo objeto). Neste âmbito,
são propostas novas técnicas para a computação de uma representação
multi-câmara multi-modal de transformação de perspectiva inversa,
para a execução de correcção de côr entre imagens de forma a
obter mosaicos de qualidade, ou para a geração de uma representação
de cena baseada em primitivas poligonais, capaz de lidar com grandes
quantidades de dados 3D e 2D, tendo inclusivamente a capacidade
de refinar a representação à medida que novos dados sensoriais são
recebidos.The main object of this thesis is the study of algorithms for automatic information
processing and representation, in particular information provided
by onboard sensors (2D and 3D), to be used in the context of
driving assistance. The work focuses on some of the problems facing
todays Autonomous Driving (AD) systems and Advanced Drivers Assistance
Systems (ADAS). The document is composed of two parts.
The first part describes the design, construction and development of
three robotic prototypes, including remarks about onboard sensors, algorithms
and software architectures. These robots were used as test
beds for testing and validating the developed techniques; additionally,
they have participated in several autonomous driving competitions with
very good results. The second part of this document presents several
algorithms for generating intermediate representations of the raw
sensor data. They can be used to enhance existing pattern recognition,
detection or navigation techniques, and may thus benefit future
AD or ADAS applications. Since vehicles often contain a large amount
of sensors of different natures, intermediate representations are particularly
advantageous; they can be used for tackling problems related
with the diverse nature of the data (2D, 3D, photometric, etc.), with the
asynchrony of the data (multiple sensors streaming data at different
frequencies), or with the alignment of the data (calibration issues, different
sensors providing different measurements of the same object).
Within this scope, novel techniques are proposed for computing a multicamera
multi-modal inverse perspective mapping representation, executing
color correction between images for obtaining quality mosaics, or
to produce a scene representation based on polygonal primitives that
can cope with very large amounts of 3D and 2D data, including the
ability of refining the representation as new information is continuously
received
Motion Planning For Micro Aerial Vehicles
A Micro Aerial Vehicle (MAV) is capable of agile motion in 3D making it an ideal platform for developments of planning and control algorithms. For fully autonomous MAV systems, it is essential to plan motions that are both dynamically feasible and collision-free in cluttered environments. Recent work demonstrates precise control of MAVs using time-parameterized trajectories that satisfy feasibility and safety requirements. However, planning such trajectories is non-trivial, especially when considering constraints, such as optimality and completeness. For navigating in unknown environments, the capability for fast re-planning is also critical. Considering all of these requirements, motion planning for MAVs is a challenging problem. In this thesis, we examine trajectory planning algorithms for MAVs and present methodologies that solve a wide range of planning problems. We first introduce path planning and geometric control methods, which produce spatial paths that are inadequate for high speed flight, but can be used to guide trajectory optimization. We then describe optimization-based trajectory planning and demonstrate this method for solving navigation problems in complex 3D environments. When the initial state is not fixed, an optimization-based method is prone to generate sub-optimal trajectories. To address this challenge, we propose a search-based approach using motion primitives to plan resolution complete and sub-optimal trajectories. This algorithm can also be used to solve planning problems with constraints such as motion uncertainty, limited field-of-view and moving obstacles. The proposed methods can run in real time and are applicable for real-world autonomous navigation, even with limited on-board computational resources. This thesis includes a carefully analysis of the strengths and weaknesses of our planning paradigm and algorithms, and demonstration of their performance through simulation and experiments
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