Designing an aerial robot for hover-and-stare surveillance

Oh, Paul; Joyce, Malcolm J.; Gallagher, Julia

doi:10.1109/icar.2005.1507428

Cited by 15 publications

(8 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our case, we are interested in developing a swarm behavior that uses the advantages of indoor flying vehicles, rather than terrestrial ones, in emergency situations. For example, these vehicles can avoid many obstacles that limit ground vehicles and enable sensor data to be obtained from a vantage point [15][16][17][18][19].…”

Section: State Of the Artmentioning

confidence: 99%

Energy-Efficient Swarm Behavior for Indoor UAV Ad-Hoc Network Deployment

et al. 2018

View full text Add to dashboard Cite

Building an ad-hoc network in emergency situations can be crucial as a primary tool or even when used prior to subsequent operations. The use of mini and micro Unmanned Aerial Vehicles (UAVs) is increasing because of the wide range of possibilities they offer. Moreover, they have been proven to bring sustainability to many applications, such as agriculture, deforestation and wildlife conservation, among others. Therefore, creating a UAV network for an unknown environment is an important task and an active research field. In this article, a mobility model for the creation of ad-hoc networks using UAVs will be presented. This model will be based on pheromones for robust navigation. We will focus mainly on developing energy-efficient behavior, which is essential for this type of vehicle. Although there are in the literature several models of mobility for ad-hoc network creation, we find that either they are not adapted to the specific energy requirements of UAVs or the proposed motion models are unrealistic or not sufficiently robust for final implantation. We will present and analyze the operation of a distributed swarm behavior able to create an ad-hoc network. Then, an analytical model of the swarm energy consumption will be proposed. This model will provide a mechanism to effectively predict the energy consumption needed for the deployment of the network prior to its implementation. Determining the use of the mobility behavior is a requirement to establish and maintain a communication channel for the required time. Finally, this analytical model will be experimentally validated and compared to the Random Waypoint (RWP) mobility strategy.

show abstract

Section: State Of the Artmentioning

confidence: 99%

Energy-Efficient Swarm Behavior for Indoor UAV Ad-Hoc Network Deployment

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Amazon is planning to deliver packages into customers hands in thirty minutes or less using hexarotors [1]. Moreover, such aerial vehicles are moving from passive tasks like inspection [2] and surveillance [3] into active tasks like grasping [4] and aerial manipulation [5], [6], [7], [8]. This changing scenario requires the introduction not only of rules and regulation, but also of safe controllers.…”

Section: Introductionmentioning

confidence: 99%

Emergency landing for a quadrotor in case of a propeller failure: A PID based approach

Lippiello

Ruggiero

Serra

2014

2014 IEEE International Symposium on Safety, Security, and Rescue Robotics (2014)

View full text Add to dashboard Cite

A controller dealing with the failure of a quadrotor's motor is presented in this paper. Supposing that the failure has been already detected by the system, the quadrotor is modelled as a birotor with fixed propellers and it is controlled to follow a planned emergency landing trajectory. Theory shows that, in such a configuration, the aerial vehicle is allowed to reach any position in the Cartesian space dropping the possibility to control the yaw angle. Simulations are presented to confirm the presented methodology.

show abstract

“…Swarms of flying robots are promising for search in indoor environments where the ability to move above debris or obstacles such as furniture is advantageous (Nardi et al 2006, Oh et al 2005, Rudol et al 2008, Hoffmann et al 2004, Melhuish and Welsby 2002. Such a swarm can establish a robot sensor and communication network that can impart navigation aid to other robots or humans, e.g.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient indoor search by swarms of simulated flying robots without global information

2010

View full text Add to dashboard Cite

Swarms of flying robots are a promising alternative to ground-based robots for search in indoor environments with advantages such as increased speed and the ability to fly above obstacles. However, there are numerous problems that must be surmounted including limitations in available sensory and on-board processing capabilities, and low flight endurance. This paper introduces a novel strategy to coordinate a swarm of flying robots for indoor exploration that significantly increases energy efficiency. The presented algorithm is fully distributed and scalable. It relies solely on local sensing and low-bandwidth communication, and does not require absolute positioning, localisation, or explicit world-models. It assumes that flying robots can temporarily attach to the ceiling, or land on the ground for efficient surveillance over extended periods of time. To further reduce energy consumption, the swarm is incrementally deployed by launching one robot at a time. Extensive simulation experiments demonstrate that increasing the time between consecutive robot launches significantly lowers energy consumption by reducing total swarm flight time, while also decreasing collision probability. As a trade-off, however, the search time increases with increased inter-launch periods. These effects are stronger in more complex environments. The proposed localisation-free strategy provides an energy efficient search behaviour adaptable to different environments or timing constraints.

show abstract

Designing an aerial robot for hover-and-stare surveillance

Cited by 15 publications

References 7 publications

Energy-Efficient Swarm Behavior for Indoor UAV Ad-Hoc Network Deployment

Energy-Efficient Swarm Behavior for Indoor UAV Ad-Hoc Network Deployment

Emergency landing for a quadrotor in case of a propeller failure: A PID based approach

Energy-efficient indoor search by swarms of simulated flying robots without global information

Contact Info

Product

Resources

About