Cameron Finucane

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The Linear Temporal Logic MissiOn Planning (LTLMoP) toolkit is a software package designed to assist in the rapid development, implementation, and testing of high-level robot controllers. In this toolkit, structured English and Linear Temporal Logic are used to write high-level reactive task specifications, which are then automatically transformed into(More)
This paper presents an implementation of an effective EEG-based Brain Computer Interface design as the control mechanism for an immersive 3-D game. The BCI is based on the application of the steady-state visual evoked potential (SSVEP) generated in response to phase-reversing checkerboard patterns. Real-time game control and signal processing is facilitated(More)
This paper addresses the challenge of enabling nonexpert users to command robots to perform complex high-level tasks using natural language. It describes an integrated system that combines the power of formal methods with the accessibility of natural language, providing correct-by-construction controllers for high-level specifications that can be(More)
While highly constrained language can be used for robot control, robots that can operate as fully autonomous subordinate agents communicating via rich language remain an open challenge. Toward this end, we developed an autonomous system that supports natural, continuous interaction with the operator through language before, during, and after mission(More)
This paper presents an integrated system for generating, troubleshooting, and executing correct-byconstruction controllers for autonomous robots using natural language input, allowing non-expert users to command robots to perform high-level tasks. This system unites the power of formal methods with the accessibility of natural language, providing(More)
The Linear Temporal Logic MissiOn Planning (LTLMoP) toolkit is a software package designed to generate a controller that guarantees a robot satisfies a task specification written by the user in structured English. The controller can be implemented on either a simulated or physical robot. This video illustrates the use of LTLMoP to generate a(More)
The use of formal methods for synthesis has recently enabled the automated construction of verifiable high-level robot control. Most approaches use a discrete abstraction of the underlying continuous domain, and make assumptions about the physical execution of actions given a discrete implementation; examples include when actions will complete relative to(More)
This paper addresses the challenge of creating correct-by-construction controllers for robots whose actions are of varying execution durations. Recently, Linear Temporal Logic synthesis has been used to construct robot controllers for performing high-level tasks. During continuous execution of these controllers by a physical robot, one or more low-level(More)
This paper illustrates the Linear Temporal Logic MissiOn Planning (LTLMoP) toolkit. LTLMoP is an open source software package that transforms high-level specifications for robot behavior, captured using a structured English grammar, into a robot controller that guarantees the robot will complete its task, if the task is feasible. If the task cannot be(More)
This paper shows an example application of the LTLMoP mission planning toolkit, in which an Aldebaran Nao and an iRobot Create each play a very basic game of hide-and-seek. Introduction Most robots currently available to the consumer, medical, and industrial markets are single-purpose, pre-programmed devices. However, as hardware technology matures, we will(More)