Sigmund Hennum Høeg

I'm a Ph.D. graduate at the Robotics and Automation Group at NTNU, where I focus on applying learning methods to robotic control.

I did my master's degree at the Norwegian University of Science and Technology (NTNU), where I did an academic exchange to ETH Zürich.

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Research

I've done projects in Reinforcement Learning for robotic grasping, applying Language Models for decision making. I'm currently interested in Imitiation Learning for robotic control.

Streaming Diffusion Policy: Fast Policy Synthesis with Variable Noise Diffusion Models
Sigmund Hennum Høeg, Yilun Du, Olav Egeland
Accepted to 2025 IEEE International Conference on Robotics & Automation (ICRA), 2025

Introduction of a fast diffusion-based robotic control policy. The method enables real-time robot control while maintaining the quality of diffusion-based policies, demonstrating strong performance across various robotic manipulation tasks.

More than eleven thousand words: Towards using language models for robotic sorting of unseen objects into arbitrary categories
Sigmund Hennum Høeg, Lars Tingelstad
Workshop on language and robotics at CoRL 2022, 2022

Analyzing the performance of language models on sorting unseen objects into arbitrary categories. Measuring performance metrics, and discussing failure modes.

Learning to grasp: A study of learning-based methods for robotic grasping
Sigmund Hennum Høeg
NTNU Open, 2022

A study of Reinforcement Learning methods for robotic grasping. We compare the performance of different methods, and discuss the challenges of applying RL algorithms to robotic grasping. Using Robosuite as a simulated benchmark.