10 papers
Structured Learning for Electromagnetic Field Modeling and Real-Time Inversion
Antonio Bernardes, Jasan Zughaibi, Michael Muehlebach +1
Precise magnetic field modeling is fundamental to the closed-loop control of electromagnetic navigation systems (eMNS) and the analytical Multipole Expansion Model (MPEM) is the cu…
Expanding the Workspace of Electromagnetic Navigation Systems Using Dynamic Feedback for Single- and Multi-agent Control
Jasan Zughaibi, Denis von Arx, Maurus Derungs +5
Electromagnetic navigation systems (eMNS) enable a number of magnetically guided surgical procedures. A challenge in magnetically manipulating surgical tools is that the effective…
Fast Non-Log-Concave Sampling under Nonconvex Equality and Inequality Constraints with Landing
Kijung Jeon, Michael Muehlebach, Molei Tao
Sampling from constrained statistical distributions is a fundamental task in various fields including Bayesian statistics, computational chemistry, and statistical physics. This ar…
Embodied Intelligence for Sustainable Flight: A Soaring Robot with Active Morphological Control
Ghadeer Elmkaiel, Syn Schmitt, Michael Muehlebach
Achieving both agile maneuverability and high energy efficiency in aerial robots, particularly in dynamic wind environments, remains challenging. Conventional thruster-powered syst…
Zeroth-Order Optimization Finds Flat Minima
Liang Zhang, Bingcong Li, Kiran Koshy Thekumparampil +3
Zeroth-order methods are extensively used in machine learning applications where gradients are infeasible or expensive to compute, such as black-box attacks, reinforcement learning…
Constraint-Aware Diffusion Guidance for Robotics: Real-Time Obstacle Avoidance for Autonomous Racing
Hao Ma, Sabrina Bodmer, Andrea Carron +2
Diffusion models hold great potential in robotics due to their ability to capture complex, high-dimensional data distributions. However, their lack of constraint-awareness limits t…