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cs.RO2025

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…

cs.RO2025

Towards Tighter Convex Relaxation of Mixed-Integer Programs: Leveraging Logic Network Flow for Task and Motion Planning

Xuan Lin, Jiming Ren, Yandong Luo +2

This paper proposes an optimization-based task and motion planning framework, named "Logic Network Flow," that integrates temporal logic specifications into mixed-integer programs…

cs.RO2025

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…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024

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…