9 papers · 1 filter
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…
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…
Terrain-Aware Model Predictive Control of Heterogeneous Bipedal and Aerial Robot Coordination for Search and Rescue Tasks
Abdulaziz Shamsah, Jesse Jiang, Ziwon Yoon +2
Humanoid robots offer significant advantages for search and rescue tasks, thanks to their capability to traverse rough terrains and perform transportation tasks. In this study, we…
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…
A Unified Approach to Multi-task Legged Navigation: Temporal Logic Meets Reinforcement Learning
Jesse Jiang, Samuel Coogan, Ye Zhao
This study examines the problem of hopping robot navigation planning to achieve simultaneous goal-directed and environment exploration tasks. We consider a scenario in which the ro…
Bipedal Safe Navigation over Uncertain Rough Terrain: Unifying Terrain Mapping and Locomotion Stability
Kasidit Muenprasitivej, Jesse Jiang, Abdulaziz Shamsah +2
We study the problem of bipedal robot navigation in complex environments with uncertain and rough terrain. In particular, we consider a scenario in which the robot is expected to r…
LTL-D*: Incrementally Optimal Replanning for Feasible and Infeasible Tasks in Linear Temporal Logic Specifications
Jiming Ren, Haris Miller, Karen M. Feigh +2
This paper presents an incremental replanning algorithm, dubbed LTL-D*, for temporal-logic-based task planning in a dynamically changing environment. Unexpected changes in the envi…