D. Angley

Publications16
h-index6
Citations75
Highly Influential Citations4
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Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment
TLDR
A search algorithm for turbulent environments which falls into the class of cognitive (infotaxi) algorithms which is carried out in a centralised replicated fusion architecture assuming all-to-all communication.
Spatio-temporal tracking from natural language statements using outer probability theory
Gaussian Mixture Multitarget Multisensor Bernoulli Tracker for Multistatic Sonobuoy Fields
TLDR
This study presents a Gaussian mixture version of a multitarget-multisensor (MS) Bayesian-type tracker developed specifically for multistatic sonobuoy fields, which is the optimal Bayesian MS filter for a single target in clutter.
Identifying Cognitive Radars - Inverse Reinforcement Learning Using Revealed Preferences
TLDR
An inverse reinforcement learning problem involving “us” versus an “enemy” radar equipped with a Bayesian tracker, and a stochastic optimization algorithm to optimize the probe signal.
Non-myopic sensor scheduling for multistatic sonobuoy fields
TLDR
A stationary scheduling algorithm for sonobuoy fields called the continuous probability states algorithm is described, which replaces a full partially observed Markov decision process by a computationally feasible Markov process by focusing on probability of target detection.
Sensor scheduling for target tracking in large multistatic sonobuoy fields
TLDR
A new long term sensor scheduling algorithm for sonobuoy fields is described, called the continuous probability states algorithm, that reduces the scheduling search space by keeping track of the probability that a target is undetected, rather than modelling all possible detection outcomes, which reduces the computation complexity of the algorithm.
A random finite set approach to occupancy-grid SLAM
TLDR
An occupancy-grid algorithm for SLAM which deals with this type of imperfect sensor measurements using the random finite set theoretical framework is presented, formulated as a Rao-Blackwellised particle filter, where the robot pose is estimated using the sequential Monte Carlo method, while the map is calculated analytically.
Search for targets in a risky environment using multi‐objective optimisation
This study develops an online unmanned aerial vehicle (UAV) path-planning strategy for autonomous search and localisation of targets in a risky environment that simultaneously optimises two…
Scheduling of Multistatic Sonobuoy Fields Using Multi-Objective Optimization
TLDR
A novel scheduling framework based on multi-objective optimization poses the two tasks of the sonobuoy field-tracking and searching-as separate, competing, objective functions and proposes a characterization of scheduling based on Pareto optimality.
Bayesian multitarget tracker for multistatic sonobuoy systems
TLDR
The paper presents the latest stage in the development of a robust multitarget tracker to be deployed in a large multistatic sonobuoy system and, due to the highly nonlinear measurements, implemented using the sequential Monte Carlo method.
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