In this project, we study robot swarms’ application to agriculture. Specifically, we focus on (i) persis- tent coverage, (ii) fuel constraints, and (iii) failures. We present a baseline Mixed-Integer Linear Pro- gramming (MILP) model, as well as heuristic algorithms trading the optimality of MILP for scalability and resilience against failures. We compare the solutions based on metrics about visitation frequency and coverage. Finally, we present visualization, simulation, and real-world evaluation (using Khepera IV robots) to validate our solutions. A summarized version of our methodology and results is available at  https://nestlab-bae-mqp-2024.github.io

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Holmes, Samara
• Cummings, Claire
• Idikut, Yasar

Subject

• Environment
• Food
• Sustainability
• Computing
• Project-Based Learning
• Security

Publisher

• Worcester Polytechnic Institute

Identifier

• 122015
• E-project-042924-131807

Stichwort

• Persistent Coverage
• Failure Constraints
• Visitation Frequency
• MILP(Mixed-Integer Linear Programming)
• Fuel Constraints
• Multi-Robot Systems

Advisor

• Pinciroli, Carlo

Year

• 2024

Sponsor

• BAE Systems

UN Sustainable Development Goals

• 2 - Zero Hunger
• 3 - Good Health and Well-being

Date created

• 2024-04-29

Resource type

• Major Qualifying Project

Major

• Robotics Engineering
• Computer Science

Source

• E-project-042924-131807

Rights statement

• In Copyright

Zuletzt geändert

• 2024-05-20