LoCUS: A Multi-Robot Loss-Tolerant Algorithm for Surveying Volcanic Plumes

@article{Erickson2020LoCUSAM,
  title={LoCUS: A Multi-Robot Loss-Tolerant Algorithm for Surveying Volcanic Plumes},
  author={John J. Erickson and Abhinav Aggarwal and G. Matthew Fricke and Melanie E. Moses},
  journal={2020 Fourth IEEE International Conference on Robotic Computing (IRC)},
  year={2020},
  pages={113-120}
}
Measurement of volcanic CO2 flux by a drone swarm poses special challenges. Drones must be able to follow gas concentration gradients while tolerating frequent drone loss. We present the LoCUS algorithm as a solution to this problem and prove its robustness. LoCUS relies on swarm coordination and self-healing to solve the task. As a point of contrast we also implement the MoBS algorithm, derived from previously published work, which allows drones to solve the task independently. We compare the… 

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References

SHOWING 1-10 OF 25 REFERENCES

Moth-inspired chemical plume tracing on an autonomous underwater vehicle

This paper presents a behavior-based adaptive mission planner to trace a chemical plume to its source and reliably declare the source location and describes the methods and results from experiments conducted in November 2002, using a plume of Rhodamine dye developed in a turbulent fluid flow.

From Insects to Micro Air Vehicles - A Comparison of Reactive Plume Tracking Strategies

The experimental evaluation shows that, under certain environmental conditions, insect like behavior in gas-sensitive UAVs is feasible in real-world environments.

Dynamics of Outgassing and Plume Transport Revealed by Proximal Unmanned Aerial System (UAS) Measurements at Volcán Villarrica, Chile

Volcanic gas emissions are intimately linked to the dynamics of magma ascent and outgassing and, on geological time scales, constitute an important source of volatiles to the Earth's atmosphere.

Flocking algorithm for autonomous flying robots.

This paper presents an abstract mathematical model of an autonomous flying robot, which takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects, and presents two decentralized control algorithms based on a simple self-propelled flocking model of animal collective motion.

ARGoS: A modular, multi-engine simulator for heterogeneous swarm robotics

Results show that ARGoS can simulate about 10,000 simple wheeled robots 40% faster than real-time, and paves the way for a new approach to parallelism in robotics simulation.

Ignorance is Not Bliss: An Analysis of Central-Place Foraging Algorithms

This work compares the performance of three Central-Place Foraging Algorithms, variants of which have been shown to work well in real robots: spiral-based, rotating-spoke, and random-ballistic, and suggests the following efficiency ranking from best to worst: spiral, spoke, and the stochastic ballistic algorithm.

Gradient climbing in formation via extremum seeking and passivity‐based coordination rules

We consider a gradient climbing problem where the objective is to steer a group of vehicles to the extrema of an unknown scalar field distribution while keeping a prescribed formation. We address

Vehicle networks for gradient descent in a sampled environment

This work formulate and study a coordinated control strategy for a group of autonomous vehicles to descend or climb an environmental gradient using measurements of the environment together with relative position measurements of nearest neighbors.

Fault-tolerant flocking for a group of autonomous mobile robots