Anthony Finn

Multiple UAVs path planning algorithms: a comparative study

Unmanned aerial vehicles (UAVs) are used in team for detecting targets and keeping them in its sensor range. There are various algorithms available for searching and monitoring targets. The complexity of the search algorithm increases if the number of nodes is increased. This paper focuses on multi UAVs path planning and Path Finding algorithms. Number of Path Finding and Search algorithms was applied to various environments, and their performance compared. The number of searches and also the computation time increases as the number of nodes increases. The various algorithms studied are Dijkstra’s algorithm, Bellman Ford’s algorithm, Floyd-Warshall’s algorithm and the AStar algorithm. These search algorithms were compared. The results show that the AStar algorithm performed better than the other search algorithms. These path finding algorithms were compared so that a path for communication can be established and monitored.

Path planning and obstacle avoidance for autonomous mobile robots: a review

Recent advances in the area of mobile robotics caused growing attention of the armed forces, where the necessity for unmanned vehicles being able to carry out the “dull and dirty” operations, thus avoid endangering the life of the military personnel. UAV offers a great advantage in supplying reconnaissance data to the military personnel on the ground, thus lessening the life risk of the troops. In this paper we analyze various techniques for path planning and obstacle avoidance and cooperation issues for multiple mobile robots. We also present a generic dynamics and control model for steering a UAV along a collision free path from a start to a goal position.

Acoustic sense & avoid for UAV's

Based on successful results obtained from a laboratory prototype and real-world experiments, this paper discusses an innovative technique for providing small Unmanned Aerial Vehicles (UAVs) with 360 degree field of view sense and avoid capability. The proposed approach allows an aircraft equipped with appropriate acoustic sensors and processing to detect and accurately track other aircraft, manned or unmanned, in their proximity, determine whether or not they pose a threat, and, if necessary, take appropriate autonomous, quick-reaction measures to avoid them. The prototype is based on reliable, low-cost hardware that is platform independent, omni-directional, passive and draws little power. The technology is equally effective in day and night time conditions and also offers the prospect of retrofit to manned aircraft to provide them with a similar capacity to detect and avoid UAVs.

Three-Dimensional UAV-Based Atmospheric Tomography

AbstractThis paper presents a method for tomographically reconstructing spatially varying three-dimensional atmospheric temperature profiles and wind velocity fields based on passive acoustic travel time measurements between a small unmanned aerial vehicle (UAV) and ground-based microphones. A series of simulations are presented to provide an indication of the performance of the technique. The parametric fields are modeled as the weighted sum of radial basis functions (RBFs) or Fourier series, which also allow local meteorological measurements made at the UAV and ground receivers to supplement any time delay observations. The technique has potential for practical applications such as boundary layer meteorology and theories of atmospheric turbulence and wave propagation through a turbulent atmosphere.

Design Challenges for an Autonomous Cooperative of UAVs

The Defence Science & Technology Organisation (DSTO), which is part of the Australian Department of Defence, is developing a research capability that uses small, inexpensive, autonomous uninhabited air vehicles (UAVs) to detect, identify, target, track, and electronically engage ground-based targets such as radars. The UAVs, which act autonomously and cooperatively, use a geographically distributed and heterogenous mix of relatively unsophisticated electronic warfare (EW) sensors and other miniaturised payloads networked together to deliver a distributed situational awareness picture that can be shared across the command echelons. If the many design challenges are overcome, the cooperation and networking of these platforms and payloads could provide results superior to those of the significantly more expensive, platform-centric systems, but with the added advantage of robustness. This paper outlines the challenges relating to autonomy, supervision, and control that the developers face and reports on the development of DSTOs multi-UAV cooperative to date.

Frequency estimation for 3D atmospheric tomography using unmanned aerial vehicles

Spatially varying three-dimensional atmospheric temperature profiles and wind velocity fields may be derived by observing the acoustic signature of an Unmanned Aerial Vehicle (UAV) as it flies over ground-based microphones. The Doppler shift between the UAV and the ground microphones is used to estimate the acoustic propagation times and the atmospheric parameters are then estimated from the derived acoustic propagation times. The estimates may be supplemented by local meteorological measurements made at the UAV and/or the ground receivers. The technique models the atmospheric temperature and wind speed profiles as a 3-dimensional continuous array of Radial Basis Functions. This technique has potential for atmospheric research and practical applications such as boundary layer meteorology, theories of atmospheric turbulence and wave propagation through a turbulent atmosphere. This paper describes how the propagation time and speed of sound is derived from the Doppler frequency. It then describes the method for performing tomographic inversion and then provides simulation results.

Centralized path planning for unmanned aerial vehicles with a heterogeneous mix of sensors

This paper is concerned with real-time optimal UAV path planning in a multi-emitter geolocation environment. All UAVs are assumed to be controlled by a central processing unit. A UAV waypoint-update/steering algorithm is developed based on maximizing the determinant of Fisher information matrix for localization of stationary emitters. Soft and hard geometric constraints for threat/collision avoidance are also implemented. An effective joint path optimization and dynamic sensor allocation algorithm is proposed to handle communication bandwidth constraints. The performance of the developed steering algorithm is illustrated with extensive simulation examples.

The feasibility of unmanned aerial vehicle-based acoustic atmospheric tomography

A technique for remotely monitoring the near-surface air temperature and wind fields up to altitudes of 1 km is presented and examined. The technique proposes the measurement of sound spectra emitted by the engine of a small unmanned aerial vehicle using sensors located on the aircraft and the ground. By relating projected and observed Doppler shifts in frequency and converting them into effective sound speed values, two- and three-dimensional spatially varying atmospheric temperature and wind velocity fields may be reconstructed using tomography. The feasibility and usefulness of the technique relative to existing unmanned aerial vehicle-based meteorological techniques using simulation and trials is examined.

A Novel Closed-Form Estimator for 3D TMA Using Heterogeneous Sensors

This paper considers the problem of three-dimensional target motion analysis using a combination of bearing, elevation, and time difference of arrival (TDOA) measurements. We propose a hybrid closed-form solution based on the weighted instrumental variables for this highly nonlinear problem. The proposed solution avoids the high computational complexity and convergence problems associated with iterative estimators. Furthermore, the simulation results suggest that the proposed estimator is nearly efficient, since its performance is very close to the best achievable performance as predicted by the Cramer-Rao lower bound.

Evaluating autonomous ground-robots

The robotics community benefits from common test methods and metrics of performance to focus their research. As a result, many performance tests, competitions, demonstrations, and analyses have been devised to measure the autonomy, intelligence, and overall effectiveness of robots. These range from robot soccer (football) to measuring the performance of a robot in computer simulations. However, many resultant designs are narrowly focused oroptimized against the specific tasks under consideration. In the Multi-Autonomous Ground-robotic International Challenge (MAGIC) 2010, the need to transition the technology beyond the laboratory and into contexts for which it had not specifically been designed or tested meant that a performance evaluation scheme was needed that avoided domain-specific tests. However, the scheme still had to retain the capacity to deliver an impartial, consistent, objective, and evidence-based assessment that rewarded individual and multivehicle autonomy. It was also important to maximize the understanding and outcomes for technologists, sponsors, and potential usersgained through after-action review. The need for real-time, simultaneous, and continuous tracking of multiple interacting entities in an urban environment and over 250,000 square meters in real time compounded the complexity of the task. This paper describes the scheme used to progressively down-select and finally rank the teams competing in this complex and “operationally realistic” challenge.