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Ingmar Posner

Ingmar Posner

Professor of Applied AI

Principal Investigator - A2I

Biography

Ingmar leads the Applied Artificial Intelligence Lab (A2I) at Oxford University. His goal is to enable robots to robustly and effectively operate in complex, real-world environments. His research is guided by a vision to create machines which constantly improve through experience. In doing so Ingmar’s work explores a number of intellectual challenges at the heart of robot learning, such as unsupervised scene interpretation and action inference, machine introspection in perception and decision making, data efficient learning from demonstration, transfer learning and the learning of complex tasks via a curriculum of less complex ones. All the while Ingmar’s research remains grounded in real-world robotics applications such as manipulation, autonomous driving, logistics and space exploration. Ingmar is recipient of a number of best paper awards at leading international venues in robotics research and AI. He is a founding Director of the Oxford Robotics Institute, which has forged an international reputation for excellence in robotics research. In 2014 Ingmar co-founded Oxbotica, a leading provider of mobile autonomy software solutions.

Teaching Material: C18 Mobile Robotics & Navigation Code Pack: available here.

Most Recent Publications

Offline Adaptation of Quadruped Locomotion using Diffusion Models

Offline Adaptation of Quadruped Locomotion using Diffusion Models

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A Review of Differentiable Simulators

A Review of Differentiable Simulators

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Oscillating latent dynamics in robot systems during walking and reaching

Oscillating latent dynamics in robot systems during walking and reaching

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Gaitor: Learning a Unified Representation Across Gaits for Real-World Quadruped Locomotion

Gaitor: Learning a Unified Representation Across Gaits for Real-World Quadruped Locomotion

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TWIST: Teacher-Student World Model Distillation for Efficient Sim-to-Real Transfer

TWIST: Teacher-Student World Model Distillation for Efficient Sim-to-Real Transfer

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