Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment
- B. Ristic, D. Angley, B. Moran, J. Palmer
- Computer ScienceItalian National Conference on Sensors
- 1 April 2017
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.
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…
Spatio-temporal tracking from natural language statements using outer probability theory
- A. Bishop, J. Houssineau, D. Angley, B. Ristic
- Computer ScienceInformation Sciences
- 1 October 2018
Sensor scheduling for target tracking in large multistatic sonobuoy fields
- D. Angley, S. Suvorova, S. Simakov
- Computer ScienceIEEE International Conference on Acoustics…
- 1 March 2017
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.
Gaussian Mixture Multitarget Multisensor Bernoulli Tracker for Multistatic Sonobuoy Fields
- B. Ristic, D. Angley, S. Simakov
- Engineering
- 7 December 2017
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
- V. Krishnamurthy, D. Angley, R. Evans, B. Moran
- Computer ScienceIEEE Transactions on Signal Processing
- 1 December 2019
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.
A random finite set approach to occupancy-grid SLAM
- B. Ristic, D. Angley, Daniel D. Selvaratnam, B. Moran, J. Palmer
- EngineeringFusion
- 5 July 2016
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.
Non-myopic sensor scheduling for multistatic sonobuoy fields
- D. Angley, B. Ristic, S. Simakov
- Business
- 8 September 2017
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.
Scheduling of Multistatic Sonobuoy Fields Using Multi-Objective Optimization
- C. Gilliam, B. Ristic, S. Simakov
- Computer ScienceIEEE International Conference on Acoustics…
- 18 April 2018
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.
RRT* Trajectory Scheduling Using Angles-Only Measurements for AUV Recovery
- Xuezhi Wang, Simon Williams, B. Moran
- Computer ScienceFusion
- 1 July 2019
A random sampling based trajectory planning algorithm is proposed that incorporates an information theoretic cost into a rapid-exploring random tree trajectory planning framework thus allowing the AUV to both localize and reach the recovery vessel.
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