Max Robotics — Global Service Robot Directory + US Certification

About

Mark Edmonds is a leading researcher in human-robot interaction and artificial intelligence, with a focus on building trustworthy, socially aware autonomous systems. His work centers on three key areas: explainable AI, bidirectional human-robot value alignment, and causal learning for robotics. Edmonds’ most influential contribution is his 2019 paper, “A tale of two explanations,” which has garnered 132 citations and provides a foundational framework for how robots can explain their actions to foster human trust—a critical step for deploying AI in high-stakes environments. He further advanced the field with his 2022 work on “in situ bidirectional human-robot value alignment” (74 citations), demonstrating how robots can learn and negotiate human values in real-time during collaborative tasks. Edmonds has also made notable contributions to robot manipulation, using imitation learning to handle complex, multi-stage tasks like opening medicine bottles (66 citations), and pioneered early brain-machine interfaces for robotic arm control. His recent work on “Actional-Perceptual Causality” aims to establish a unified framework for causal learning in AI, addressing a major gap in the field. Through these achievements, Edmonds is shaping how robots become not just functional, but truly collaborative partners.