meSch: Multi-Agent Energy-Aware Scheduling for Task Persistence

meSch is a scheduling algorithm for a team of autonomous robots that operate on long-term persistent tasks. The proposed framework accounts for the limited battery capacity of the robots and ensures that the robots return to charge their batteries one at a time at the single charging station.

Demo Video

Summary

The protocol is:

• Applicable to general nonlinear robot models under certain assumptions
• Does not require robots to be deployed at different times
• Handles robots with different discharge rates
• Supports mobile charging stations with state uncertainty

Feasibility of the algorithm for ensuring persistent charging is established under certain assumptions. Efficacy is validated through simulation and hardware experiments.

Requirements

• Julia 1.6 or later

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/meSch.git
   cd meSch

2. Start Julia and activate the project:

   using Pkg
   Pkg.activate(".")
   Pkg.instantiate()

Usage

Running Simulations

The code includes Jupyter notebooks for different experimental scenarios:

Notebook	Description
notebooks/meSch-2Q.ipynb	Two quadrotors with fixed charging station
notebooks/meSch-3Q.ipynb	Three quadrotors with fixed charging station
notebooks/meSch-mobile.ipynb	Two quadrotors with mobile charging station (rover)
notebooks/benchmarking.ipynb	Benchmarking experiments

Run the notebooks from the project root. The first cell activates the project and installs dependencies.

Programmatic Usage

# Load dependencies and experiment module
include("src/utils.jl")
include("src/ExpDynamicsLibrary.jl")
include("src/RefTrajectoryLibrary.jl")
include("src/ExpControllerLibrary.jl")
include("src/ExpmeSchFlylab_2.jl")  # or ExpmeSchFlylab_3, ExpmeSchDI2_mobile

# Run 2-quad simulation (see notebook for initial conditions)
sol, params = meSchExpDIFL.simulate(quad_ic, t0, t_max, discharge_rate)

Project Structure

meSch/
├── src/
│   ├── meSch.jl              # Main module
│   ├── ExpmeSchFlylab_2.jl   # 2-quad meSch experiments
│   ├── ExpmeSchFlylab_3.jl   # 3-quad meSch experiments
│   ├── ExpmeSchDI2_mobile.jl # Mobile charging station experiments
│   ├── ExpDynamicsLibrary.jl # Robot dynamics (quadrotor, double-integrator)
│   ├── ExpControllerLibrary.jl # MPC and geometric controller
│   ├── RefTrajectoryLibrary.jl # Reference trajectories (Lissajous, figure-8)
│   ├── utils.jl              # Utilities (quaternions, etc.)
│   ├── Visualization.jl      # MeshCat visualization
│   └── utils/                # Mesh assets for visualization
├── notebooks/
│   ├── meSch-2Q.ipynb
│   ├── meSch-3Q.ipynb
│   ├── meSch-mobile.ipynb
│   └── benchmarking.ipynb
├── Project.toml
└── README.md

Robot Model

• High-level: Double integrator model with Convex MPC for planning
• Low-level: Quadrotor dynamics with geometric controller tracking
• Battery: Linear discharge model with state of charge (SoC)

License

See LICENSE for details.

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Publication & Citation

If you use this code in your research, please cite:

meSch: Multi-Agent Energy-Aware Scheduling for Task Persistence
Kaleb Ben Naveed, An Dang, Rahul Kumar, Dimitra Panagou
2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Pages 21458–21465 | DOI: 10.1109/IROS60139.2025.11247605

BibTeX:

@INPROCEEDINGS{11247605,
  author={Ben Naveed, Kaleb and Dang, An and Kumar, Rahul and Panagou, Dimitra},
  booktitle={2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  title={meSch: Multi-Agent Energy-Aware Scheduling for Task Persistence},
  year={2025},
  pages={21458-21465},
  doi={10.1109/IROS60139.2025.11247605}
}