1 citations · 1 across the 4 of their papers we have counts for
6 papers
A Decade of Learning-Based Control: From Theoretic Foundations to Practical Deployment
Angela P. Schoellig, Matthias A. Müller, Sebastian Trimpe +8
Motivated by ten years of Learning-Based Control Invited Sessions at the IEEE Conference on Decision and Control (CDC), this tutorial paper reviews key advances at the intersection…
Learning from Demonstrations Meets Symbolic Control - A Supervisory Control Architecture for Formal Certification of Learned Motion
Ashok Kumar, Mahathi Anand, Angela P. Schoellig +2
Dynamical system (DS)-based learning from demonstration generates flexible robot motions, but existing guarantees rely on certificate generation to obtain formal guarantees of safe…
CSymPlan: Certified Symbolic Planning and Control for High-DOF Manipulators
Aditya Narendra, Ashok Kumar Saini, Mahathi Anand +3
Robot manipulators are commonly engineered around a decoupled motion-generation stack: a planner computes a collision-free path and a lower-level controller tracks the resulting re…
Learning from Demonstrations over Riemannian Manifolds using Neural ODEs: An Extended Abstract
Diana Cuervo Espinosa, Mahathi Anand, Angela P. Schoellig
Learning from demonstratins (LfD) is usually performed over Euclidean spaces, while the robot state, e.g. orientation, naturally evolves over curved spaces. Therefore, to ensure na…
Safe and Stable Neural Network Dynamical Systems for Robot Motion Planning
Allen Emmanuel Binny, Mahathi Anand, Hugo T. M. Kussaba +4
Learning safe and stable robot motions from demonstrations remains a challenge, especially in complex, nonlinear tasks involving dynamic, obstacle-rich environments. In this paper,…
Density Matrix-based Dynamics for Quantum Robotic Swarms
Maria Mannone, Mahathi Anand, Peppino Fazio +1
In a robotic swarm, parameters such as position and proximity to the target can be described in terms of probability amplitudes. This idea led to recent studies on a quantum approa…