10 research outputs found
A Distributed Pipeline for Scalable, Deconflicted Formation Flying
Reliance on external localization infrastructure and centralized coordination
are main limiting factors for formation flying of vehicles in large numbers and
in unprepared environments. While solutions using onboard localization address
the dependency on external infrastructure, the associated coordination
strategies typically lack collision avoidance and scalability. To address these
shortcomings, we present a unified pipeline with onboard localization and a
distributed, collision-free motion planning strategy that scales to a large
number of vehicles. Since distributed collision avoidance strategies are known
to result in gridlock, we also present a decentralized task assignment solution
to deconflict vehicles. We experimentally validate our pipeline in simulation
and hardware. The results show that our approach for solving the optimization
problem associated with motion planning gives solutions within seconds in cases
where general purpose solvers fail due to high complexity. In addition, our
lightweight assignment strategy leads to successful and quicker formation
convergence in 96-100% of all trials, whereas indefinite gridlocks occur
without it for 33-50% of trials. By enabling large-scale, deconflicted
coordination, this pipeline should help pave the way for anytime, anywhere
deployment of aerial swarms.Comment: 8 main pages, 1 additional page, accepted to RA-L and IROS'2
Robust MADER: Decentralized Multiagent Trajectory Planner Robust to Communication Delay in Dynamic Environments
Communication delays can be catastrophic for multiagent systems. However,
most existing state-of-the-art multiagent trajectory planners assume perfect
communication and therefore lack a strategy to rectify this issue in real-world
environments. To address this challenge, we propose Robust MADER (RMADER), a
decentralized, asynchronous multiagent trajectory planner robust to
communication delay. By always keeping a guaranteed collision-free trajectory
and performing a delay check step, RMADER is able to guarantee safety even
under communication delay. We perform an in-depth analysis of trajectory
deconfliction among agents, extensive benchmark studies, and hardware flight
experiments with multiple dynamic obstacles. We show that RMADER outperforms
existing approaches by achieving a 100% success rate of collision-free
trajectory generation, whereas the next best asynchronous decentralized method
only achieves 83% success.Comment: 8 pagers, 13 figures,. arXiv admin note: substantial text overlap
with arXiv:2209.1366
Formation Flight in Dense Environments
Formation flight has a vast potential for aerial robot swarms in various
applications. However, existing methods lack the capability to achieve fully
autonomous large-scale formation flight in dense environments. To bridge the
gap, we present a complete formation flight system that effectively integrates
real-world constraints into aerial formation navigation. This paper proposes a
differentiable graph-based metric to quantify the overall similarity error
between formations. This metric is invariant to rotation, translation, and
scaling, providing more freedom for formation coordination. We design a
distributed trajectory optimization framework that considers formation
similarity, obstacle avoidance, and dynamic feasibility. The optimization is
decoupled to make large-scale formation flights computationally feasible. To
improve the elasticity of formation navigation in highly constrained scenes, we
present a swarm reorganization method which adaptively adjusts the formation
parameters and task assignments by generating local navigation goals. A novel
swarm agreement strategy called global-remap-local-replan and a formation-level
path planner is proposed in this work to coordinate the swarm global planning
and local trajectory optimizations efficiently. To validate the proposed
method, we design comprehensive benchmarks and simulations with other
cutting-edge works in terms of adaptability, predictability, elasticity,
resilience, and efficiency. Finally, integrated with palm-sized swarm platforms
with onboard computers and sensors, the proposed method demonstrates its
efficiency and robustness by achieving the largest scale formation flight in
dense outdoor environments.Comment: Submitted for IEEE Transactions on Robotic
SLAM: Decentralized and Distributed Collaborative Visual-inertial SLAM System for Aerial Swarm
In recent years, aerial swarm technology has developed rapidly. In order to
accomplish a fully autonomous aerial swarm, a key technology is decentralized
and distributed collaborative SLAM (CSLAM) for aerial swarms, which estimates
the relative pose and the consistent global trajectories. In this paper, we
propose SLAM: a decentralized and distributed () collaborative SLAM
algorithm. This algorithm has high local accuracy and global consistency, and
the distributed architecture allows it to scale up. SLAM covers swarm
state estimation in two scenarios: near-field state estimation for high
real-time accuracy at close range and far-field state estimation for globally
consistent trajectories estimation at the long-range between UAVs. Distributed
optimization algorithms are adopted as the backend to achieve the goal.
SLAM is robust to transient loss of communication, network delays, and
other factors. Thanks to the flexible architecture, SLAM has the potential
of applying in various scenarios
Meeting U.S. defense needs in the information age : an evaluation of selected comlex electronic system development methodologies
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1995.Includes bibliographical references (p. 159-167).by Alexander C. Hou.M.S
A Bibliography of NPS Space Systems Related Student Research, 2013-2022
Dudley Knox Library, Naval Postgraduate School.Approved for Public Release; distribution is unlimite
3D-in-2D Displays for ATC.
This paper reports on the efforts and accomplishments
of the 3D-in-2D Displays for ATC project at the end of Year 1.
We describe the invention of 10 novel 3D/2D visualisations that
were mostly implemented in the Augmented Reality ARToolkit.
These prototype implementations of visualisation and interaction
elements can be viewed on the accompanying video. We have
identified six candidate design concepts which we will further
research and develop. These designs correspond with the early
feasibility studies stage of maturity as defined by the NASA
Technology Readiness Level framework. We developed the
Combination Display Framework from a review of the literature,
and used it for analysing display designs in terms of display
technique used and how they are combined. The insights we
gained from this framework then guided our inventions and the
human-centered innovation process we use to iteratively invent.
Our designs are based on an understanding of user work
practices. We also developed a simple ATC simulator that we
used for rapid experimentation and evaluation of design ideas.
We expect that if this project continues, the effort in Year 2 and 3
will be focus on maturing the concepts and employment in a
operational laboratory settings