kevinkawchak/robotarium-nurse-patient-study: v0.1

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Authors: Kevin Kawchak, Claude, renoschubert
Cited by: 0

Abstract

Summary Added dual-experiment support to the web simulator with a dropdown selector for the 14-robot swarm and 2-robot nurse-patient experiments, dynamic phase timeline and legend adaptation, and CI hardening with explicit dependency management via requirements.txt and smoke tests for both experiment scripts across Python 3.10, 3.11, and 3.12. README updated with a direct simulation link and three text diagrams covering architecture, arena layout, and experiment timeline perspectives. Features Web simulator v3.1 experiment selector: choose 14-robot swarm or 2-robot nurse-patient from a dropdown, no file upload needed. Dynamic legend and phase timeline: automatically switches between Doctor/Patient and Nurse/Patient labels and phase names based on loaded experiment. FRAME_LOG reset between simulation runs for clean replay without page reload. requirements.txt for explicit NumPy dependency management across CI and local environments. CI workflow now tests both Exp_01a_12Feb26.py (14-robot) and main.py (2-robot) as separate smoke test steps. README restructured with web simulator link at top, three text diagrams (Simulator Architecture, Arena Top-Down View, Experiment Timeline Comparison), and explicit experiment sections for both scripts. Updated docs/simulator.md with v0.3.1 architecture diagram and v0.3.0-to-v0.3.1 comparison table. Contributors @kevinkawchak @claude Notes Use the web simulator dropdown to quickly switch between the 2-robot nurse-patient interaction and the 14-robot swarm triage experiment. The requirements.txt file ensures consistent NumPy versions across local development and CI. Both experiment scripts remain fully compatible with the Robotarium physical platform for direct submission.

Fields of Study & Subjects

Modular Robots and Swarm Intelligence Distributed Control Multi-Agent Systems Metaheuristic Optimization Algorithms Research

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
30 January 2026