Planejamento de caminhos suaves e seguros baseados em espuma probabilística para Sistemas Robóticos Autônomos
Planning a path for a robot to navigate between two points in a given environment and avoiding collision with obstacles is one of the main issues for autonomous robotics. The search for short paths and reduced search time are aspects of most planning methods, but in applications in which the robots...
Na minha lista:
| Autor principal: | |
|---|---|
| Outros Autores: | |
| Formato: | doctoralThesis |
| Idioma: | pt_BR |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
|
| Assuntos: | |
| Endereço do item: | https://repositorio.ufrn.br/handle/123456789/44894 |
| Tags: |
Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
|
| Resumo: | Planning a path for a robot to navigate between two points in a given environment and
avoiding collision with obstacles is one of the main issues for autonomous robotics. The
search for short paths and reduced search time are aspects of most planning methods, but
in applications in which the robots interact directly with human beings, such as assistive
robotics, ensuring a greater degree of safety associated with the movements is an essential
requirement. In this context, this thesis presents a set of new strategies for the planning
of safe paths for autonomous robots. The developed methods are essentially based on the
concepts of the probabilistic foam method (PFM). PFM is a sampling-based path planning method capable of generating paths bounded by a set of connected bubbles, which
guarantees a volumetric region in the free space for safe maneuverability. In order to
compute the bubbles, PFM requires an explicit representation of the obstacle region in the
configuration space, which is computationally impracticable considering its application
for most problems. Thus, a novel strategy to compute bubbles without representing these
obstacles regions is introduced. Besides, we present an analysis to reduce the number of
PFM parameters. To improve the quality of the paths, two optimization procedures were
implemented to reduce the path length and increase the path smoothness, maintaining a
high clearance. Novel PFM-based techniques are developed to explore different mechanisms for the propagation of the foam, aiming to ensure the planning of shorter paths with
a short search time, also guaranteeing paths with high clearance. In order to evidence
the main contributions of this thesis, some simulated experiments are performed considering the path planning for two assistive robots: The first one is a lower limb exoskeleton,
which aim at overcoming obstacles, walking up and down a stair, resulting in smooth
movements with a more anthropomorphic pattern. These results illustrate the ability of
PFM to plan safe and smooth paths for open kinematic-chain robots without the explicit
representation of the obstacle region in configuration space. Smart Walker is the second
robot considered in this work, and it was possible to represent the planning of safe paths
for a mobile robot with differential drive, in addition to show some aspects of the paths
planned by the new introduced methods. |
|---|