24 research outputs found
Voliro: An Omnidirectional Hexacopter With Tiltable Rotors
Extending the maneuverability of unmanned areal vehicles promises to yield a
considerable increase in the areas in which these systems can be used. Some
such applications are the performance of more complicated inspection tasks and
the generation of complex uninterrupted movements of an attached camera. In
this paper we address this challenge by presenting Voliro, a novel aerial
platform that combines the advantages of existing multi-rotor systems with the
agility of omnidirectionally controllable platforms. We propose the use of a
hexacopter with tiltable rotors allowing the system to decouple the control of
position and orientation. The contributions of this work involve the mechanical
design as well as a controller with the corresponding allocation scheme. This
work also discusses the design challenges involved when turning the concept of
a hexacopter with tiltable rotors into an actual prototype. The agility of the
system is demonstrated and evaluated in real- world experiments.Comment: Submitted to Robotics and Automation Magazin
Autonomous Reality Modelling for Cultural Heritage Sites employing cooperative quadrupedal robots and unmanned aerial vehicles
Nowadays, the use of advanced sensors, such as terrestrial 3D laser scanners,
mobile LiDARs and Unmanned Aerial Vehicles (UAV) photogrammetric imaging, has
become the prevalent practice for 3D Reality Modeling and digitization of
large-scale monuments of Cultural Heritage (CH). In practice, this process is
heavily related to the expertise of the surveying team, handling the laborious
planning and time-consuming execution of the 3D mapping process that is
tailored to the specific requirements and constraints of each site. To minimize
human intervention, this paper introduces a novel methodology for autonomous 3D
Reality Modeling for CH monuments by employing au-tonomous biomimetic
quadrupedal robotic agents and UAVs equipped with the appropriate sensors.
These autonomous robotic agents carry out the 3D RM process in a systematic and
repeatable ap-proach. The outcomes of this automated process may find
applications in digital twin platforms, facilitating secure monitoring and
management of cultural heritage sites and spaces, in both indoor and outdoor
environments
Actively Mapping Industrial Structures with Information Gain-Based Planning on a Quadruped Robot
In this paper, we develop an online active mapping system to enable a
quadruped robot to autonomously survey large physical structures. We describe
the perception, planning and control modules needed to scan and reconstruct an
object of interest, without requiring a prior model. The system builds a voxel
representation of the object, and iteratively determines the Next-Best-View
(NBV) to extend the representation, according to both the reconstruction itself
and to avoid collisions with the environment. By computing the expected
information gain of a set of candidate scan locations sampled on the as-sensed
terrain map, as well as the cost of reaching these candidates, the robot
decides the NBV for further exploration. The robot plans an optimal path
towards the NBV, avoiding obstacles and un-traversable terrain. Experimental
results on both simulated and real-world environments show the capability and
efficiency of our system. Finally we present a full system demonstration on the
real robot, the ANYbotics ANYmal, autonomously reconstructing a building facade
and an industrial structure
Online Informative Path Planning for Active Information Gathering of a 3D Surface
This paper presents an online informative path planning approach for active
information gathering on three-dimensional surfaces using aerial robots. Most
existing works on surface inspection focus on planning a path offline that can
provide full coverage of the surface, which inherently assumes the surface
information is uniformly distributed hence ignoring potential spatial
correlations of the information field. In this paper, we utilize manifold
Gaussian processes (mGPs) with geodesic kernel functions for mapping surface
information fields and plan informative paths online in a receding horizon
manner. Our approach actively plans information-gathering paths based on recent
observations that respect dynamic constraints of the vehicle and a total flight
time budget. We provide planning results for simulated temperature modeling for
simple and complex 3D surface geometries (a cylinder and an aircraft model). We
demonstrate that our informative planning method outperforms traditional
approaches such as 3D coverage planning and random exploration, both in
reconstruction error and information-theoretic metrics. We also show that by
taking spatial correlations of the information field into planning using mGPs,
the information gathering efficiency is significantly improved.Comment: 7 pages, 7 figures, to be published in 2021 IEEE International
Conference on Robotics and Automation (ICRA