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Papers by Michael Goodrich
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
ACM Transactions on Human-Robot Interaction
As development of robots with the ability to self-assess their proficiency for accomplishing task... more As development of robots with the ability to self-assess their proficiency for accomplishing tasks continues to grow, metrics are needed to evaluate the characteristics and performance of these robot systems and their interactions with humans. This proficiency-based human-robot interaction (HRI) use case can occur before, during, or after the performance of a task. This article presents a set of metrics for this use case, driven by a four-stage cyclical interaction flow: (1) robot self-assessment of proficiency (RSA), (2) robot communication of proficiency to the human (RCP), (3) human understanding of proficiency (HUP), and (4) robot perception of the human’s intentions, values, and assessments (RPH). This effort leverages work from related fields including explainability, transparency, and introspection, by repurposing metrics under the context of proficiency self-assessment. Considerations for temporal level (a priori, in situ, and post hoc) on the metrics are reviewed, as are th...
Adaptive Agents and Multi-Agents Systems, May 4, 2015
Adaptive Agents and Multi-Agents Systems, May 5, 2014
Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 2017
Engineering Psychology and Cognitive Ergonomics: Performance, Emotion and Situation Awareness, 2017
Unmanned Systems Technology XX, 2018
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Algorithms used in networking, operation research and optimization can be created using bio-inspi... more Algorithms used in networking, operation research and optimization can be created using bio-inspired swarm behaviors, but it is difficult to mimic swarm behaviors that generalize through diverse environments. State-machine-based artificial collective behaviors evolved by standard Grammatical Evolution (GE) provide promise for general swarm behaviors but may not scale to large problems. This paper introduces an algorithm that evolves problem-specific swarm behaviors by combining multi-agent grammatical evolution and Behavior Trees (BTs). We present a BT-based BNF grammar, supported by different fitness function types, which overcomes some of the limitations in using GEs to evolve swarm behavior. Given human-provided, problem-specific fitness-functions, the learned BT programs encode individual agent behaviors that produce desired swarm behaviors. We empirically verify the algorithm's effectiveness on three different problems: single-source foraging, collective transport, and nest...
2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)
Journal of Human-Robot Interaction, 2015
2015 Swarm/Human Blended Intelligence Workshop (SHBI), 2015
A mission to Mars will be composed of several groups that need to interact effectively. Scientist... more A mission to Mars will be composed of several groups that need to interact effectively. Scientists on Earth, supervisors in a habitat on Mars, and a surface exploration team on Mars will all require different views of information. This position paper proposes a multiple perspective interface paradigm which implements augmented virtuality and multiple camera perspectives to clearly present these views.
Proceeding of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction - HRI '06, 2006
AIAA Infotech@Aerospace Conference, 2009
2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012
Infotech@Aerospace 2012, 2012
Unmanned Systems Technology XVI, 2014
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
ACM Transactions on Human-Robot Interaction
As development of robots with the ability to self-assess their proficiency for accomplishing task... more As development of robots with the ability to self-assess their proficiency for accomplishing tasks continues to grow, metrics are needed to evaluate the characteristics and performance of these robot systems and their interactions with humans. This proficiency-based human-robot interaction (HRI) use case can occur before, during, or after the performance of a task. This article presents a set of metrics for this use case, driven by a four-stage cyclical interaction flow: (1) robot self-assessment of proficiency (RSA), (2) robot communication of proficiency to the human (RCP), (3) human understanding of proficiency (HUP), and (4) robot perception of the human’s intentions, values, and assessments (RPH). This effort leverages work from related fields including explainability, transparency, and introspection, by repurposing metrics under the context of proficiency self-assessment. Considerations for temporal level (a priori, in situ, and post hoc) on the metrics are reviewed, as are th...
Adaptive Agents and Multi-Agents Systems, May 4, 2015
Adaptive Agents and Multi-Agents Systems, May 5, 2014
Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 2017
Engineering Psychology and Cognitive Ergonomics: Performance, Emotion and Situation Awareness, 2017
Unmanned Systems Technology XX, 2018
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Algorithms used in networking, operation research and optimization can be created using bio-inspi... more Algorithms used in networking, operation research and optimization can be created using bio-inspired swarm behaviors, but it is difficult to mimic swarm behaviors that generalize through diverse environments. State-machine-based artificial collective behaviors evolved by standard Grammatical Evolution (GE) provide promise for general swarm behaviors but may not scale to large problems. This paper introduces an algorithm that evolves problem-specific swarm behaviors by combining multi-agent grammatical evolution and Behavior Trees (BTs). We present a BT-based BNF grammar, supported by different fitness function types, which overcomes some of the limitations in using GEs to evolve swarm behavior. Given human-provided, problem-specific fitness-functions, the learned BT programs encode individual agent behaviors that produce desired swarm behaviors. We empirically verify the algorithm's effectiveness on three different problems: single-source foraging, collective transport, and nest...
2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)
Journal of Human-Robot Interaction, 2015
2015 Swarm/Human Blended Intelligence Workshop (SHBI), 2015
A mission to Mars will be composed of several groups that need to interact effectively. Scientist... more A mission to Mars will be composed of several groups that need to interact effectively. Scientists on Earth, supervisors in a habitat on Mars, and a surface exploration team on Mars will all require different views of information. This position paper proposes a multiple perspective interface paradigm which implements augmented virtuality and multiple camera perspectives to clearly present these views.
Proceeding of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction - HRI '06, 2006
AIAA Infotech@Aerospace Conference, 2009
2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012
Infotech@Aerospace 2012, 2012
Unmanned Systems Technology XVI, 2014