Michael K. Roberts

RO
h-index36
3papers
11citations
Novelty25%
AI Score27

3 Papers

ROSep 26, 2024
HARMONIC: A Framework for Explanatory Cognitive Robots

Sanjay Oruganti, Sergei Nirenburg, Marjorie McShane et al.

We present HARMONIC, a framework for implementing cognitive robots that transforms general-purpose robots into trusted teammates capable of complex decision-making, natural communication and human-level explanation. The framework supports interoperability between a strategic (cognitive) layer for high-level decision-making and a tactical (robot) layer for low-level control and execution. We describe the core features of the framework and our initial implementation, in which HARMONIC was deployed on a simulated UGV and drone involved in a multi-robot search and retrieval task.

ROSep 26, 2024
HARMONIC: Cognitive and Control Collaboration in Human-Robotic Teams

Sanjay Oruganti, Sergei Nirenburg, Marjorie McShane et al.

This paper describes HARMONIC, a cognitive-robotic architecture that integrates the OntoAgent cognitive framework with general-purpose robot control systems applied to human-robot teaming (HRT). HARMONIC incorporates metacognition, meaningful natural language communication, and explainability capabilities required for developing mutual trust in HRT. Through simulation experiments involving a joint search task performed by a heterogeneous team of two HARMONIC-based robots and a human operator, we demonstrate heterogeneous robots that coordinate their actions, adapt to complex scenarios, and engage in natural human-robot communication. Evaluation results show that HARMONIC-based robots can reason about plans, goals, and team member attitudes while providing clear explanations for their decisions, which are essential requirements for realistic human-robot teaming.

ROSep 16, 2025
HARMONIC: A Content-Centric Cognitive Robotic Architecture

Sanjay Oruganti, Sergei Nirenburg, Marjorie McShane et al.

This paper introduces HARMONIC, a cognitive-robotic architecture designed for robots in human-robotic teams. HARMONIC supports semantic perception interpretation, human-like decision-making, and intentional language communication. It addresses the issues of safety and quality of results; aims to solve problems of data scarcity, explainability, and safety; and promotes transparency and trust. Two proof-of-concept HARMONIC-based robotic systems are demonstrated, each implemented in both a high-fidelity simulation environment and on physical robotic platforms.