2026 Season Active • Next Competition: Tri-County High-Speed Sprint • Team Status: Preparing
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MOGUL TEAM#30524
Autonomous Squad#ROV-30524-MK42025-2026

Apex MK-IV Autonomous SLAM Arena Bot

Full SLAM navigation arena rover featuring 2D LiDAR point-cloud mapping, real-time trajectory optimization, and edge neural network inferencing for target isolation. Designed with an omnidirectional Mecanum platform for instantaneous zero-radius vector realignment.

ROS2 HumbleRPLiDAR A2 360°RPi5 + TeensyMecanum 4WD
Apex MK-IV Autonomous SLAM Arena Bot
Competition Ready
Mapping Update Rate
10Hz
Max Linear Speed
1.6m/s
Battery Runtime
4.5hrs
Localization Accuracy
±3cm
Weight Class

12.5 kg (Autonomous)

Main Compute

Raspberry Pi 5 + Teensy 4.1

Power Delivery

LiFePO4 4S 13.2V (20Ah)

Control Loop

ROS2 Nav2 + FastSLAM

Hardware Dissection

Interactive Robot Explorer

Tap any numbered hotspot to inspect subsystem specs, interface protocols, and design justifications.

Apex MK-IV Autonomous SLAM Arena Bot
Tap numbered tags 1-5 to switch component dossiersACTIVE: [1] RPLiDAR A2
Subsystem 01 of 05PERCEPTION

360° LiDAR Scanner

Model:Slamtec RPLiDAR A2M8
Primary Function

Spins at 10Hz to build a live 360° point cloud used for SLAM mapping and obstacle avoidance.

Selection Rationale

12m range and 10Hz scan rate is fast enough to catch fast-moving opponents at arena speed without motion blur in the point cloud.

Interface / Bus:UART 115200 baud
5 Points Total
BOM & Component Log

Bill of Materials Directory

COMPUTEQTY: 1

Raspberry Pi 5 (8GB)

Part #: RPI5-8GB

Primary ROS2 Nav2 compute running SLAM and vision inferencing.

SENSORSQTY: 1

Slamtec RPLiDAR A2M8

Part #: RPLIDAR-A2M8

360° 2D LiDAR scanner for point-cloud mapping at 10Hz.

CONTROLQTY: 1

Teensy 4.1

Part #: TEENSY-4.1

Dedicated motor control and encoder odometry microcontroller.

POWERQTY: 1

LiFePO4 4S 20Ah Pack

Part #: LFP-4S-20AH

Abuse-tolerant primary power cell with an integrated BMS.

Iterative R&D

Generational Development Timeline

MK-II Prototype2024
Raspberry Pi 4 · 2D LiDAR

First SLAM prototype, proved basic Nav2 costmap navigation at walking speed.

MK-IV Current Flagship2025-2026
RPi5 + Teensy 4.1 · Mecanum 4WD

Full Nav2 stack with YOLO object detection and omnidirectional Mecanum drive.

Sanctioned Arena Record

Competition History & Podiums

emoji_events GOLDOCT 2025

National Robotics Challenge 2025

Autonomous SLAM Division

Completed the full maze-mapping course with zero collisions and the fastest total mapping time.

National Robotics ArenaRank 1 / 22
military_tech SILVERAUG 2025

Rover Regional Challenge

Regional Autonomous

Runner-up after a costmap misread near a reflective obstacle cost time on the final leg.

Regional STEM CenterRank 2 / 30
Engineering Scientific Method

Testing & Improvement Lab Logs

LOG #2025-09-02warning

Reflective Surface Costmap Noise

PROBLEM:Reflective arena flooring caused the LiDAR to register phantom obstacles, forcing unnecessary reroutes.
TEST:Logged raw point-cloud scans across three lighting conditions to isolate the reflective floor sections.
ENGINEERING CHANGE:Added a costmap inflation filter that discounts single-frame transient returns before they reach the planner.
✓ RESULT: Phantom-obstacle reroutes dropped to zero across 20 test runs.
LOG #2025-10-14warning

Mecanum Wheel Slip on Turns

PROBLEM:Sharp strafing turns caused wheel slip that drifted odometry estimates by several centimeters per turn.
TEST:Compared encoder-only odometry against LiDAR scan-matched position over a fixed test loop.
ENGINEERING CHANGE:Fused wheel odometry with LiDAR scan matching in the localization filter instead of relying on encoders alone.
✓ RESULT: Drift reduced from 8cm to under 3cm per full lap.
Visual Archives

Robot in Action & Lab Media

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Trophy Case

Honors Awarded to Apex MK-IV

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CHAMPIONSHIP

National Robotics Challenge Gold

Fastest full-course SLAM mapping run of the 2025 season with zero collisions.

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RELIABILITY RECORD

20-Run Zero-Collision Streak

Longest consecutive collision-free test streak logged by any MOGUL TEAM autonomous platform.