activity
20102026
most citedRobust Temporal Logic Model Predictive Control

160 citations · 831 across the 126 of their papers we have counts for

collaborators

143 papers

eess.SY2026

Belief-Informed Hybrid Control with Almost-Sure Target-Set Convergence

Clinton Enwerem, Saleh Kemal, John S. Baras +1

Controlling a hybrid system to a target set under parameter uncertainty can require informative actions that temporarily drive the system state away from the specified set. We prop…

cs.RO2026

GJK-CBF: Control Barrier Functions for Convex Rigid Body Collision Avoidance on SE(3)

Yi-Hsuan Chen, Shuo Liu, Wei Xiao +2

Collision avoidance among convex bodies is a fundamental problem in robotics. Control Barrier Functions (CBFs) provide a practical framework for real-time safety filtering due to t…

eess.SY2026

Model Predictive Control for Safety-Critical Systems Using Taylor's Theorem with Lagrange Remainder

Shuo Liu, Liang Wu, Wei Xiao +2

Safety-critical Model Predictive Control (MPC) formulations based on Control Barrier Functions (CBFs) often require multiple tuning parameters and may become conservative or diffic…

eess.SY2026

Differentiable Ternary Temporal Logic Semantics with Polynomial Surrogate Networks

Ryan Matheu, Sai Sandeep Damera, John S. Baras +1

Temporal logic provides designers a formal reasoning tool for specifying complex spatio-temporal behaviors and tasks for autonomous systems. Many techniques exist for control synth…

eess.SY2026

Experimental Design for Controller Selection in Synthetic Biology

Eric Palanques-Tost, Ron Weiss, Calin Belta

Synthetic biology enables the design of genetic circuits that act as feedback controllers. These controllers are typically designed using computational models, but mismatch between…

cs.RO2026

Does Imitation Learning Preserve Temporal Robustness in Dexterous Manipulation? An Expert-Learner Comparison Across Task Execution Speeds

Clinton Enwerem, John S. Baras, Calin Belta

Dexterous manipulation policies learned by imitation are typically evaluated for robustness to variation in scenes, objects, or instructions, but their performance across task exec…