1 citations · 1 across the 18 of their papers we have counts for
20 papers
BubbleCBF: Constructive Safety for Second-Order Systems and Application to Autonomous Robot Navigation in Unknown Environments
Mani Amani, Mohammed Alyaseen, Zhirui Dai +3
Satisfying safety constraints for systems with second-order dynamics is challenging because a position constraint may require infeasible deceleration. Higher-order control barrier…
A Unified Perspective on Conformal Prediction and Wasserstein Distributionally Robust Optimization for Uncertainty Quantification
Kehan Long, Yiqi Zhao, Pol Mestres +3
Uncertainty quantification from finite data is central to machine learning, optimization, and automation systems, where decisions must remain reliable under limited samples and tes…
Contact-Aware Planning and Control of Continuum Robots in Highly Constrained Environments
Aedan Mangan, Kehan Long, Ki Myung Brian Lee +3
Continuum robots are well suited for navigating confined and fragile environments, such as vascular or endoluminal anatomy, where contact with surrounding structures is often unavo…
Control Barrier Corridors: From Safety Functions to Safe Sets
Ömür Arslan, Nikolay Atanasov
Safe autonomy is a critical requirement and a key enabler for robots to operate safely in unstructured complex environments. Control barrier functions and safe motion corridors are…
A Shared-Autonomy Construction Robotic System for Overhead Works
David Minkwan Kim, K. M. Brian Lee, Yong Hyeok Seo +11
We present the ongoing development of a robotic system for overhead work such as ceiling drilling. The hardware platform comprises a mobile base with a two-stage lift, on which a b…
Constrained Variational Inference via Safe Particle Flow
Yinzhuang Yi, Jorge Cortés, Nikolay Atanasov
We propose a control barrier function (CBF) formulation for enforcing equality and inequality constraints in variational inference. The key idea is to define a barrier functional o…
Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
Kehan Long, Jorge Cortés, Nikolay Atanasov
Establishing stability certificates for closed-loop systems under reinforcement learning (RL) policies is essential to move beyond empirical performance and offer guarantees of sys…
Variational Formulation of Particle Flow
Yinzhuang Yi, Jorge Cortés, Nikolay Atanasov
This paper provides a formulation of the log-homotopy particle flow from the perspective of variational inference. We show that the transient density used to derive the particle fl…
Safe Control of Second-Order Systems with Linear Constraints
Mohammed Alyaseen, Nikolay Atanasov, Jorge Cortes
Control barrier functions (CBFs) offer a powerful tool for enforcing safety specifications in control synthesis. This paper deals with the problem of constructing valid CBFs. Given…
Neural Configuration-Space Barriers for Manipulation Planning and Control
Kehan Long, Ki Myung Brian Lee, Nikola Raicevic +3
Planning and control for high-dimensional robot manipulators in cluttered dynamic environments require computational efficiency and robust safety guarantees. Inspired by recent adv…
Safety-Critical Control of Discontinuous Systems with Nonsmooth Safe Sets
Mohammed Alyaseen, Nikolay Atanasov, Jorge Cortes
This paper studies the design of controllers for discontinuous dynamics that ensure the safety of non-smooth sets. The safe set is represented by arbitrarily nested unions and inte…
Neural Configuration Distance Function for Continuum Robot Control
Kehan Long, Hardik Parwana, Georgios Fainekos +3
This paper presents a novel method for modeling the shape of a continuum robot as a Neural Configuration Euclidean Distance Function (N-CEDF). By learning separate distance fields…
Stabilization of Nonlinear Systems through Control Barrier Functions
Pol Mestres, Kehan Long, Melvin Leok +2
This paper proposes a control design approach for stabilizing nonlinear control systems. Our key observation is that the set of points where the decrease condition of a control Lya…
Sensor-Based Distributionally Robust Control for Safe Robot Navigation in Dynamic Environments
Kehan Long, Yinzhuang Yi, Zhirui Dai +3
We introduce a novel method for mobile robot navigation in dynamic, unknown environments, leveraging onboard sensing and distributionally robust optimization to impose probabilisti…
Distributionally Robust Policy and Lyapunov-Certificate Learning
Kehan Long, Jorge Cortes, Nikolay Atanasov
This article presents novel methods for synthesizing distributionally robust stabilizing neural controllers and certificates for control systems under model uncertainty. A key chal…
Feasibility Analysis and Regularity Characterization of Distributionally Robust Safe Stabilizing Controllers
Pol Mestres, Kehan Long, Nikolay Atanasov +1
This paper studies the well-posedness and regularity of safe stabilizing optimization-based controllers for control-affine systems in the presence of model uncertainty. When the sy…
Distributed Bayesian Estimation in Sensor Networks: Consensus on Marginal Densities
Parth Paritosh, Nikolay Atanasov, Sonia Martinez
In this paper, we aim to design and analyze distributed Bayesian estimation algorithms for sensor networks. The challenges we address are to (i) derive a distributed provably-corre…
Distributed Variational Inference for Online Supervised Learning
Parth Paritosh, Nikolay Atanasov, Sonia Martinez
Developing efficient solutions for inference problems in intelligent sensor networks is crucial for the next generation of location, tracking, and mapping services. This paper deve…
EAST: Environment Aware Safe Tracking using Planning and Control Co-Design
Zhichao Li, Yinzhuang Yi, Zhuolin Niu +1
This paper considers the problem of autonomous mobile robot navigation in unknown environments with moving obstacles. We propose a new method to achieve environment-aware safe trac…
Safe Stabilizing Control for Polygonal Robots in Dynamic Elliptical Environments
Kehan Long, Khoa Tran, Melvin Leok +1
This paper addresses the challenge of safe navigation for rigid-body mobile robots in dynamic environments. We introduce an analytic approach to compute the distance between a poly…