5 papers
Merging model-based control with multi-agent reinforcement learning for multi-agent cooperative teaming strategies
Christian Llanes, Spencer W. Jensen, Samuel Coogan
In this work, we propose a framework that combines multi-agent reinforcement learning (MARL) with model-based control to achieve safe, dynamically feasible actions in cooperative m…
Make Your VLA More Robust Without More Data By Interleaving Motion Planning
Dan BW Choe, Sundhar Vinodh Sangeetha, Samuel Coogan +1
Vision-Language-Action (VLA) models have shown remarkable progress for mobile manipulation, but their performance on long-horizon tasks remains poor. These tasks are especially cha…
Adaptive Obstacle-Aware Task Assignment and Planning for Heterogeneous Robot Teaming
Nan Li, Jiming Ren, Haris Miller +3
Multi-Agent Task Assignment and Planning (MATP) has attracted growing attention but remains challenging in terms of scalability, spatial reasoning, and adaptability in obstacle-ric…
Optimization-based Task and Motion Planning under Signal Temporal Logic Specifications using Logic Network Flow
Xuan Lin, Jiming Ren, Samuel Coogan +1
This paper proposes an optimization-based task and motion planning framework, named "Logic Network Flow", to integrate signal temporal logic (STL) specifications into efficient mix…
Accelerating Signal-Temporal-Logic-Based Task and Motion Planning of Bipedal Navigation using Benders Decomposition
Jiming Ren, Xuan Lin, Roman Mineyev +3
Task and motion planning under Signal Temporal Logic constraints is known to be NP-hard. A common class of approaches formulates these hybrid problems, which involve discrete task…