activity
20182025
most citedConstrained Inverse Optimal Control with Application to a Human Manipulation Task

45 citations · 90 across the 12 of their papers we have counts for

collaborators

13 papers

cs.RO2025

Energy-Efficient Motion Planner for Legged Robots

Alexander Schperberg, Marcel Menner, Stefano Di Cairano

We propose an online motion planner for legged robot locomotion with the primary objective of achieving energy efficiency. The conceptual idea is to leverage a placement set of foo…

eess.SY2024

Translation of Nagumo's Foundational Work on Barrier Functions: On the Location of Integral Curves of Ordinary Differential Equations

Marcel Menner, Eugene Lavretsky

In 1942, Prof. Mitio Nagumo published his seminal paper on the location of integral curves of ordinary differential equations. Nagumo's paper provides the foundation of the set inv…

cs.RO2024

Simultaneous State Estimation and Contact Detection for Legged Robots by Multiple-Model Kalman Filtering

Marcel Menner, Karl Berntorp

This paper proposes an algorithm for combined contact detection and state estimation for legged robots. The proposed algorithm models the robot's movement as a switched system, in…

eess.SY2023

Gaussian Processes with State-Dependent Noise for Stochastic Control

Marcel Menner, Karl Berntorp

This paper considers a stochastic control framework, in which the residual model uncertainty of the dynamical system is learned using a Gaussian Process (GP). In the proposed formu…

eess.SY2023

Friction-Adaptive Stochastic Nonlinear Model Predictive Control for Autonomous Vehicles

Sean Vaskov, Rien Quirynen, Marcel Menner +1

This paper addresses the trajectory-tracking problem under uncertain road-surface conditions for autonomous vehicles. We propose a stochastic nonlinear model predictive controller…

cs.RO2022

Real-to-Sim: Predicting Residual Errors of Robotic Systems with Sparse Data using a Learning-based Unscented Kalman Filter

Alexander Schperberg, Yusuke Tanaka, Feng Xu +2

Achieving highly accurate dynamic or simulator models that are close to the real robot can facilitate model-based controls (e.g., model predictive control or linear-quadradic regul…