Structured Techniques for Algorithmic Robotics (STAR) Lab

KODex

MARBLER

Realistic Benchmarks for Collaborative Heterogeneous Multi-Robot Systems

cap-comm

Generalization of Heterogeneous Multi-Robot Policies via Awareness and Communication of Capabilities

GRSTAPS

Graphically Recursive Simultaneous Task Allocation, Planning, and Scheduling (IJRR 2022)

CMTAB

Robotics: Science and Systems (RSS) 2023

CIMER

constrained-rl-dexterous-manipulation

IJCAI 2022 1st Safe RL Workshop paper

corrective-demos-dexterous-manipulation

HRI 2022 Workshop Paper

D-ITAGS

Dynamic Incremental Task Allocation Graph Search (RA-L / IROS 2023)

gt-star-lab.github.io

Structured Techniques for Algorithmic Robotics (STAR) Lab at Georgia Tech. PI: Harish Ravichandar

MARBLER-CA

MARBLER for Generalization of Heterogeneous Multi-Robot Policies via Awareness and Communication of Capabilities

Resource-Aware-Generalization

AAMAS 2022 - Extended Abstract

Q-ITAGS

Quality optimized task allocation and scheduling for muli-robot teams

Continuous-CBS

Continuous CBS - a modification of conflict based search algorithm, that allows to perform actions (move, wait) of arbitrary duration. Timeline is not discretized, i.e. is continuous.

JaxMARL_MARBLER

Multi-Agent Reinforcement Learning with JAX - Forked to add MARBLER

K-CBS-Expert

Expert of the K-CBS algorithm we're planning to use for our VMAS environment

risk_adaptive_task_allocation

IROS 2021 Paper

trait_weight_optimization

AAMAS 2023 - Extended Abstract

VectorizedMultiAgentSimulator

VMAS is a vectorized framework designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.