25 citations · 30 across the 11 of their papers we have counts for
13 papers
Autonomous Navigation and Station-Keeping on Near-Rectilinear Halo Orbits
Yuri Shimane, Karl Berntorp, Stefano Di Cairano +1
This article develops an optical navigation (OPNAV) and station-keeping pipeline for the near-rectilinear halo orbit (NRHO) in high-fidelity ephemeris model dynamics, using synthet…
Simultaneous Collision Detection and Force Estimation for Dynamic Quadrupedal Locomotion
Ziyi Zhou, Stefano Di Cairano, Yebin Wang +1
In this paper we address the simultaneous collision detection and force estimation problem for quadrupedal locomotion using joint encoder information and the robot dynamics only. W…
Meta-Learning for Physically-Constrained Neural System Identification
Ankush Chakrabarty, Gordon Wichern, Vedang M. Deshpande +3
We present a gradient-based meta-learning framework for rapid adaptation of neural state-space models (NSSMs) for black-box system identification. When applicable, we also incorpor…
Chance-Constrained Information-Theoretic Stochastic Model Predictive Control with Safety Shielding
Ji Yin, Panagiotis Tsiotras, Karl Berntorp
This paper introduces a novel nonlinear stochastic model predictive control path integral (MPPI) method, which considers chance constraints on system states. The proposed belief-sp…
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…
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…
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…
Mobility, Communication and Computation Aware Federated Learning for Internet of Vehicles
Md Ferdous Pervej, Jianlin Guo, Kyeong Jin Kim +7
While privacy concerns entice connected and automated vehicles to incorporate on-board federated learning (FL) solutions, an integrated vehicle-to-everything communication with het…
Exploiting Temporal Relations on Radar Perception for Autonomous Driving
Peizhao Li, Pu Wang, Karl Berntorp +1
We consider the object recognition problem in autonomous driving using automotive radar sensors. Comparing to Lidar sensors, radar is cost-effective and robust in all-weather condi…
Automated Controller Calibration by Kalman Filtering
Marcel Menner, Karl Berntorp, Stefano Di Cairano
This paper proposes a method for calibrating control parameters. Examples of such control parameters are gains of PID controllers, weights of a cost function for optimal control, f…
Exploiting Linear Substructure In LRKFs (Extended)
M. Greiff, K. Berntorp, A. Robertsson
We exploit knowledge of linear substructure in the linear-regression Kalman filters (LRKFs) to simplify the problem of moment matching. The theoretical results yield quantifiable a…
Path Planning using Positive Invariant Sets
Claus Danielson, Avishai Weiss, Karl Berntorp +1
We present an algorithm for steering the output of a linear system from a feasible initial condition to a desired target position, while satisfying input constraints and non-convex…
Sampling-based Algorithms for Optimal Motion Planning Using Closed-loop Prediction
Oktay Arslan, Karl Berntorp, Panagiotis Tsiotras
Motion planning under differential constraints, kinodynamic motion planning, is one of the canonical problems in robotics. Currently, state-of-the-art methods evolve around kinodyn…