37 citations · 151 across the 85 of their papers we have counts for
23 papers · 1 filter
Physics-Informed Koopman Learning for Data-Efficient System Identification of Automated Vehicle Dynamics
Hangyu Li, Yiming Meng, Zhaohui Liang +8
Understanding how a particular automated vehicle reacts to nearby traffic can improve motion prediction, control development, traffic simulation, and safety evaluation. However, co…
Akule: Fast and Scalable Multi-Robot Motion Planning via Sparse Interaction Diffusion
Manav Vora, Gokul Puthumanaillam, Aditya Penumarti +2
Diffusion models provide expressive trajectory priors for multi-robot motion planning (MRMP), but scaling them to large teams requires coordinating individual motions without expen…
Control of Markov Jump Linear Systems with Uncertain Lumpable Cluster Observations
Carlos A. F. Persiani, Ram Padmanabhan, Melkior Ornik +1
In this paper, we consider the control of Markov jump linear systems when the active system mode is not exactly known. We rather assume that this true mode is only known to belong…
Fast Direction-Conditioned Reachability for Motion Prediction Under Model Uncertainty
Hrishav Das, Melkior Ornik
To avoid collisions, a robot must repeatedly predict where nearby agents may move, usually with an imperfect model of their dynamics. Reachable sets provide such predictions, but c…
Risk-Aware Motion Planning and Control under Unknown Dynamics with Hybrid Observations
Zhiquan Zhang, Melkior Ornik
We consider robotic motion planning and control under unknown dynamics with hybrid state observations, where state measurements are available only in parts of the state space. Exis…
Safe, Real-Time Active Model Discrimination and Fault Diagnosis for Nonlinear Systems via Differentiable Reachability
Xinpei Ni, Melkior Ornik, Glen Chou +1
We present a safe, real-time algorithm for active fault diagnosis and model discrimination for uncertain continuous-time nonlinear systems with process and measurement disturbances…
When Should a Robot Replan? Regret-Guided Update Scheduling in Time-Varying MDPs
Negin Musavi, Gokul Puthumanaillam, Ruben Hernandez +2
Robots operating in non-stationary environments must continually adapt their policies as the dynamics drift, but onboard energy and compute budgets cap how often a full state estim…
Task-Aware Environment Augmentation for Reliable Navigation via Shielded Conditional Diffusion
Bharawee Phoompho, Gokul Puthumanaillam, Yan Miao +4
Reliable trajectory planning under partial observability depends not only on computing a feasible geometric path, but also on whether the robot receives informative observations wh…
Trajectory-Level Redirection Attacks on Vision-Language-Action Models
Gokul Puthumanaillam, Vardhan Dongre, Pranay Thangeda +3
Vision-language-action (VLA) policies bring natural language into closed-loop robot control, enabling robots to execute manipulation tasks directly from text instructions. The same…
Viscosity-Informed Generative Actor-Critic for High-Dimensional Stochastic Optimal Control
Alen E. Golpashin, Gokul Puthumanaillam, Melkior Ornik +1
We introduce a method for approximating viscosity solutions of stationary degenerate elliptic Hamilton--Jacobi--Bellman equations on bounded domains arising in stochastic exit-time…
Muninn: Your Trajectory Diffusion Model But Faster
Gokul Puthumanaillam, Hao Jiang, Ruben Hernandez +4
Diffusion-based trajectory planners can synthesize rich, multimodal robot motions, but their iterative denoising makes online planning and control prohibitively slow. Existing acce…
Live LTL Progress Tracking: Towards Task-Based Exploration
Noel Brindise, Cedric Langbort, Melkior Ornik
Motivated by the challenge presented by non-Markovian objectives in reinforcement learning (RL), we present a novel framework to track and represent the progress of autonomous agen…
Digital Guardians: The Past and The Future of Cyber-Physical Resilience
Saurabh Bagchi, Hyunseung Kim, Tarek Abdelzaher +20
Resilience in cyber-physical systems (CPS) is the fundamental ability to maintain safety and critical functionality despite adverse "perturbations," which includes security attacks…
Dynamic Regret in Time-varying MDPs with Intermittent Information
Negin Musavi, Melkior Ornik
We study sequential decision-making in time-varying Markov decision processes (TVMDPs) under limited update rates, where the decision-maker observes the system and updates its mode…
Input Matrix Optimization for Desired Reachable Set Warping of Linear Systems
Hrishav Das, Melkior Ornik
Shaping the reachable set of a dynamical system is a fundamental challenge in control design, with direct implications for both performance and safety. This paper considers the pro…
Energetic Resilience under Temporal Logic Specifications
Ratnangshu Das, Ram Padmanabhan, Melkior Ornik +1
In environments with uncertainties or undesirable influences, control systems can require additional energy to achieve their task while remaining resilient to these influences. In…
Resource-Constrained Shortest Path with Polytopic Reset Sets
Khaled Surur, Melkior Ornik
This paper investigates the problem of computing the shortest path between two states under resource constraints in environments with resource-replenishment regions. Namely, the le…
Finite-time Reachability for Constrained, Partially Uncontrolled Nonlinear Systems
Ram Padmanabhan, Melkior Ornik
This paper presents a technique to drive the state of a constrained nonlinear system to a specified target state in finite time, when the system suffers a partial loss in control a…
Hierarchical Motion Planning and Control under Unknown Nonlinear Dynamics via Predicted Reachability
Zhiquan Zhang, Melkior Ornik
Autonomous motion planning under unknown nonlinear dynamics requires learning system properties while navigating toward a target. In this work, we develop a hierarchical planning-c…
Amortizing Trajectory Diffusion with Keyed Drift Fields
Gokul Puthumanaillam, Melkior Ornik
Diffusion-based trajectory planners can synthesize rich, multimodal action sequences for offline reinforcement learning, but their iterative denoising incurs substantial inference-…
SCoUT: Scalable Communication via Utility-Guided Temporal Grouping in Multi-Agent Reinforcement Learning
Manav Vora, Gokul Puthumanaillam, Hiroyasu Tsukamoto +1
Communication can improve coordination in partially observed multi-agent reinforcement learning (MARL), but learning \emph{when} and \emph{who} to communicate with requires choosin…
Navigating in Uncertain Environments with Heterogeneous Visibility
Jongann Lee, Melkior Ornik
Navigating an environment with uncertain connectivity requires a strategic balance between minimizing the cost of traversal and seeking information to resolve map ambiguities. Unli…
The Continuous p-Dispersion Problem in Three Dimensions
Sanjay Manoj, Melkior Ornik
The Continuous p-Dispersion Problem (CpDP) with boundary constraints asks for the placement of a fixed number of points in a compact subset of Euclidean space such that the minimum…