15 papers
Multi-Agent Planning with Spatio-Temporal and Topological Constraints using STL-GO
Sheryl Paul, Vidisha Kudalkar, Anand Balakrishnan +3
Multi-agent planning problems arise in a variety of engineering applications, such as multi-robot wildfire fighting and unmanned aerial inspection in factories. A particular challe…
Conformal Predictive Programming for Chance Constrained Optimization
Yiqi Zhao, Xinyi Yu, Matteo Sesia +2
We propose conformal predictive programming (CPP), a framework to solve chance constrained optimization problems, i.e., optimization problems with constraints that are functions of…
Learning Gait-Aware Quadruped Locomotion with Temporal Logic Specifications
Merve Atasever, Cagan Bakirci, Alfredo Reina Corona +2
Reinforcement learning (RL) for quadruped locomotion commonly depends on fixed, hand-crafted, and Markovian reward functions that limit both interpretability of learned policies an…
An Algebraic Framework for Quantitative Semantics of Spatio-Temporal Logic with Graph Operators
Sheryl Paul, Vidisha Kudalkar, Anand Balakrishnan +3
Spatio-Temporal Logic with Graph Operators (STL-GO) extends Signal Temporal Logic (STL) to multi-agent systems via graph operators that count neighboring agents satisfying a proper…
Guiding Neuro-Symbolic Scenario Generation with Spatio-Temporal Logic
Lorenzo Bonin, Francesco Giacomarra, Luca Bortolussi +2
The rapid advancement of autonomous driving (AD) technologies has outpaced the development of robust safety evaluation methods. Conventional testing relies on exposing AD systems t…
Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints
Junyang Cai, Weimin Huang, Brendan Long +4
Motion-planning problems with temporal-logic or chance constraints are often encoded as mixed-integer linear programs (MILPs). Although these encodings provide rigorous specificati…