Partitioned searching and deconfliction: Analysis and flight tests

Searching a complex environment for a hidden target is a common problem encountered by many autonomous systems. Many modern autonomous systems use a hierarchical structure for mission management where different algorithms perform different tasks to give agents desired behavior. This work investigate...

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Bibliographic Details
Main Authors: Lum, C, Vagners, J, Jung Soon Jang, Vian, J
Format: Conference Proceeding
Language:English
Subjects:
Aerospace simulation
Bayesian methods
Control systems
Mobile robots
Object detection
Partitioning algorithms
Probability density function
Remotely operated vehicles
Search problems
System testing
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Description
Summary:Searching a complex environment for a hidden target is a common problem encountered by many autonomous systems. Many modern autonomous systems use a hierarchical structure for mission management where different algorithms perform different tasks to give agents desired behavior. This work investigates a search policy that guarantees both an exhaustive search of the map and conflict free paths of all agents. Agents formulate control decisions for a fixed number of time steps using a modular algorithm that allows parameterizations of agent capabilities. High fidelity simulation and flight test data using multiple autonomous vehicles are used to verify and validate the algorithms in real time.
ISSN:0743-1619
2378-5861
DOI:10.1109/ACC.2010.5531472