Publications (11)
Koopman-inspired Implicit Backward Reachable Sets for Unknown Nonlinear Systems
Haldun Balim, Antoine Aspeel, Zexiang Liu +1
Koopman liftings have been successfully used to learn high dimensional linear approximations for autonomous systems for prediction purposes, or for control systems for leveraging l…
A Single Diffusion-Policy Controller for Multi-Task Block Pushing with Zero-Shot Sim-to-Real Transfer
Haitong Ma, Haldun Balim, Yang Hu +2
Diffusion policies have shown promising empirical performance in representing and learning complex maneuvers for robots using behavior cloning (BC). In this paper, we explore train…
Model-Based Diffusion Sampling for Predictive Control in Offline Decision Making
Haldun Balim, Na Li, Yilun Du
Offline decision-making via diffusion models often produces trajectories that are misaligned with system dynamics, limiting their reliability for control. We propose Model Predicti…
EFE: End-to-end Frame-to-Gaze Estimation
Haldun Balim, Seonwook Park, Xi Wang +2
Despite the recent development of learning-based gaze estimation methods, most methods require one or more eye or face region crops as inputs and produce a gaze direction vector as…
Learning to Adapt: Representation-Based Reinforcement Learning for Multi-Task Skill Transfer
Aryan Naveen, Haitong Ma, Haldun Balim +1
Reinforcement learning has achieved remarkable success in learning complex control policies, yet its applicability remains limited due to sample inefficiency and poor generalizatio…
From Data to Predictive Control: A Framework for Stochastic Linear Systems with Output Measurements
Haldun Balim, Andrea Carron, Melanie N. Zeilinger +1
We introduce data to predictive control, D2PC, a framework to facilitate the design of robust and predictive controllers from data. The proposed framework is designed for discrete-…
Decentralized Diffusion Policy Learning for Enhanced Exploration in Cooperative Multi-agent Reinforcement Learning
Yuyang Zhang, Haldun Balim, Na Li
Cooperative multi-agent reinforcement learning (MARL) involves complex agent interactions and requires effective exploration strategies. A prominent class of MARL algorithms, decen…
Flexible Locomotion Learning with Diffusion Model Predictive Control
Runhan Huang, Haldun Balim, Heng Yang +1
Legged locomotion demands controllers that are both robust and adaptable, while remaining compatible with task and safety considerations. However, model-free reinforcement learning…
Stochastic Data-Driven Predictive Control: Chance-Constraint Satisfaction with Identified Multi-step Predictors
Haldun Balim, Andrea Carron, Melanie N. Zeilinger +1
We propose a novel data-driven stochastic model predictive control framework for uncertain linear systems with noisy output measurements. Our approach leverages multi-step predicto…
A Model-Based Approach to Imitation Learning through Multi-Step Predictions
Haldun Balim, Yang Hu, Yuyang Zhang +1
Imitation learning is a widely used approach for training agents to replicate expert behavior in complex decision-making tasks. However, existing methods often struggle with compou…
Can Transformers Learn Optimal Filtering for Unknown Systems?
Haldun Balim, Zhe Du, Samet Oymak +1
Transformer models have shown great success in natural language processing; however, their potential remains mostly unexplored for dynamical systems. In this work, we investigate t…