# Decomposition-based Hierarchical Task Allocation and Planning for Multi-Robots under Hierarchical Temporal Logic Specifications

arXiv: https://arxiv.org/abs/2308.10393 · HTML: https://mlsanity.com/paper/2308.10393/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 46 references that are in the map.
- First posted on arXiv 20 Aug 2023.

## Builds on (most cited first, 11 of 11)

- [Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery](https://mlsanity.com/paper/2110.14891/) (2021)
- [STyLuS*: A Temporal Logic Optimal Control Synthesis Algorithm for Large-Scale Multi-Robot Systems](https://mlsanity.com/paper/1809.08345/) (2018)
- [Multi-Goal Multi-Agent Pickup and Delivery](https://mlsanity.com/paper/2208.01223/) (2022)
- [An Abstraction-Free Method for Multi-Robot Temporal Logic Optimal Control Synthesis](https://mlsanity.com/paper/1909.00526/) (2019)
- [Multirobot Coordination with Counting Temporal Logics](https://mlsanity.com/paper/1810.13087/) (2018)
- [Robust Multi-Agent Coordination from CaTL+ Specifications](https://mlsanity.com/paper/2210.01732/) (2022)
- [Multi-Agent Planning under Local LTL Specifications and Event-Based Synchronization](https://mlsanity.com/paper/1610.08380/) (2016)
- [Fast Decomposition of Temporal Logic Specifications for Heterogeneous Teams](https://mlsanity.com/paper/2010.00030/) (2020)
- [Time Minimization and Online Synchronization for Multi-agent Systems under Collaborative Temporal Tasks](https://mlsanity.com/paper/2208.07756/) (2022)
- [Distributed motion coordination for multi-robot systems under LTL specifications](https://mlsanity.com/paper/2103.09111/) (2021)
- [Hierarchical Multi-robot Strategies Synthesis and Optimization under Individual and Collaborative Temporal Logic Specifications](https://mlsanity.com/paper/2110.11162/) (2021)

## Built on by (most cited first, 3 of 3)

- [Physics-Aware Combinatorial Assembly Sequence Planning using Data-free Action Masking](https://mlsanity.com/paper/2408.10162/) (2024)
- [Simultaneous Task Allocation and Planning for Multi-Robots under Hierarchical Temporal Logic Specifications](https://mlsanity.com/paper/2401.04003/) (2024)
- [Rule-based High-Level Coaching for Goal-Conditioned Reinforcement Learning in Search-and-Rescue UAV Missions Under Limited-Simulation Training](https://mlsanity.com/paper/2604.26833/) (2026)

## Abstract (arXiv)

Past research into robotic planning with temporal logic specifications, notably Linear Temporal Logic (LTL), was largely based on a single formula for individual or groups of robots. But with increasing task complexity, LTL formulas unavoidably grow lengthy, complicating interpretation and specification generation, and straining the computational capacities of the planners. A recent development has been the hierarchical representation of LTL~citeluo2024simultaneous that contains multiple temporal logic specifications, providing a more interpretable framework. However, the proposed planning algorithm assumes the independence of robots within each specification, limiting their application to multi-robot coordination with complex temporal constraints. In this work, we formulated a decomposition-based hierarchical framework. At the high level, each specification is first decomposed into a set of atomic sub-tasks. We further infer the temporal relations among the sub-tasks of different specifications to construct a task network. Subsequently, a Mixed Integer Linear Program is used to assign sub-tasks to various robots. At the lower level, domain-specific controllers are employed to execute sub-tasks. Our approach was experimentally applied to domains of navigation and manipulation. The simulation demonstrated that our approach can find better solutions using less runtimes.