Overview: A Hierarchical Framework for Plan Generation and Execution in Multi-Robot Systems
Hang Ma, Wolfgang Hönig, Liron Cohen, Tansel Uras, Hong Xu, T. K. Satish Kumar, Nora Ayanian, Sven Koenig
- Year
- 2018
- Access
- Open access
Abstract
The authors present an overview of a hierarchical framework for coordinating task- and motion-level operations in multirobot systems. Their framework is based on the idea of using simple temporal networks to simultaneously reason about precedence/causal constraints required for task-level coordination and simple temporal constraints required to take some kinematic constraints of robots into account. In the plan-generation phase, the framework provides a computationally scalable method for generating plans that achieve high-level tasks for groups of robots and take some of their kinematic constraints into account. In the plan-execution phase, the framework provides a method for absorbing an imperfect plan execution to avoid time-consuming re-planning in many cases. The authors use the multirobot path-planning problem as a case study to present the key ideas behind their framework for the long-term autonomy of multirobot systems.
Keywords
Related papers
Dynamic reconfiguration in multi-robot agent systems using embedded language models
Shokhikha Amalana Murdivien, Jongsu Park, Jumyung Um
Robotics and Computer-Integrated Manufacturing · 2026
Hierarchical decision-making for UAVs’ game via LLM enhanced multi-agent reinforcement learning
Xinyu Dong, Bo Li, Guangyu Zhang +2 more
Aerospace Science and Technology · 2026
Formation optimization and obstacle avoidance decision-making methods for cooperative coverage search of multi-UUVs in underwater wreck areas
Haomiao Yu, Zeyuan Zhang, Yantian Ma
Robotics and Autonomous Systems · 2026
Human-in-the-Loop Swarms: A Bionic Swarm Approach to Real-World Soil Mapping
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu +3 more
2026