SumoBots

Overview

An autonomous competition robot combining a lightweight CAD chassis with a sub-10 ms embedded C/C++ control loop. The design won Best Movement Algorithm at the 2025 McMaster SumoBots competition.

Problem

The team needed a robot capable of rapidly sensing opponents, making control decisions, and performing reliably in a physically constrained competitive setting.

Objectives

• Detect and react quickly to opponents
• Build robust autonomous behavior
• Balance sensing, control quality, and physical performance
• Iterate quickly under competition deadlines

System Architecture

An embedded control system integrates sensors, decision logic, and control behavior into a competitive robot platform optimized for detection, maneuvering, and contact.

Hardware

• competition robot platform
• onboard sensors
• chassis
• motor/drive hardware

Software

• C++
• embedded logic

Algorithms / Processing

• sensor fusion
• autonomous behavior logic

Key Decisions and Tradeoffs

• Balanced responsiveness with control stability
• Worked within weight and chassis constraints
• Tuned behavior for real-world contact and uncertainty rather than ideal conditions only

Biggest Challenge

The biggest challenge was getting the robot to behave reliably in dynamic, contact-heavy conditions. This required iteration across both software logic and system-level design choices.

Validation and Testing

• robot behavior testing
• iterative tuning
• competition-style evaluation
• subsystem checks

Impact

The chassis was 20% lighter without sacrificing durability or maneuverability, and the robot won Best Movement Algorithm at the 2025 McMaster SumoBots competition.

Next Improvements

• Deepen sensing robustness
• Improve strategy logic
• Continue refining maneuverability and response behavior