6 papers
Diffusion-Based Impedance Learning for Contact-Rich Manipulation Tasks
Noah Geiger, Tamim Asfour, Neville Hogan +1
Learning-based methods excel at robot motion generation but remain limited in contact-rich physical interaction. Impedance control provides stable and safe contact behavior but req…
Modular Robot Control with Motor Primitives
Moses C. Nah, Johannes Lachner, Neville Hogan
Despite a slow neuromuscular system, humans easily outperform modern robot technology, especially in physical contact tasks. How is this possible? Biological evidence indicates tha…
Surpassing Cosine Similarity for Multidimensional Comparisons: Dimension Insensitive Euclidean Metric
Federico Tessari, Kunpeng Yao, Neville Hogan
Advances in computational power and hardware efficiency have enabled tackling increasingly complex, high-dimensional problems. While artificial intelligence (AI) achieves remarkabl…
A Physically Consistent Stiffness Formulation for Contact-Rich Manipulation
Johannes Lachner, Moses C. Nah, Neville Hogan
Ensuring symmetric stiffness in impedance-controlled robots is crucial for physically meaningful and stable interaction in contact-rich manipulation. Conventional approaches neglec…
Divide et Impera: Decoding Impedance Strategies for Robotic Peg-in-Hole Assembly
Johannes Lachner, Federico Tessari, A. Michael West +2
This paper investigates robotic peg-in-hole assembly using the Elementary Dynamic Actions (EDA) framework, which models contact-rich tasks through a combination of submovements, os…
Combining Movement Primitives with Contraction Theory
Moses C. Nah, Johannes Lachner, Neville Hogan +1
This paper presents a modular framework for motion planning using movement primitives. Central to the approach is Contraction Theory, a modular stability tool for nonlinear dynamic…