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.
12.5 kg (Autonomous)
Raspberry Pi 5 + Teensy 4.1
LiFePO4 4S 13.2V (20Ah)
ROS2 Nav2 + FastSLAM
Interactive Robot Explorer
Tap any numbered hotspot to inspect subsystem specs, interface protocols, and design justifications.
360° LiDAR Scanner
Spins at 10Hz to build a live 360° point cloud used for SLAM mapping and obstacle avoidance.
12m range and 10Hz scan rate is fast enough to catch fast-moving opponents at arena speed without motion blur in the point cloud.
Bill of Materials Directory
Raspberry Pi 5 (8GB)
Primary ROS2 Nav2 compute running SLAM and vision inferencing.
Slamtec RPLiDAR A2M8
360° 2D LiDAR scanner for point-cloud mapping at 10Hz.
Teensy 4.1
Dedicated motor control and encoder odometry microcontroller.
LiFePO4 4S 20Ah Pack
Abuse-tolerant primary power cell with an integrated BMS.
Engineered by MOGUL TEAM
Generational Development Timeline
First SLAM prototype, proved basic Nav2 costmap navigation at walking speed.
Full Nav2 stack with YOLO object detection and omnidirectional Mecanum drive.
Competition History & Podiums
National Robotics Challenge 2025
Completed the full maze-mapping course with zero collisions and the fastest total mapping time.
Rover Regional Challenge
Runner-up after a costmap misread near a reflective obstacle cost time on the final leg.
Testing & Improvement Lab Logs
Reflective Surface Costmap Noise
Mecanum Wheel Slip on Turns
Robot in Action & Lab Media
Honors Awarded to Apex MK-IV
National Robotics Challenge Gold
Fastest full-course SLAM mapping run of the 2025 season with zero collisions.
20-Run Zero-Collision Streak
Longest consecutive collision-free test streak logged by any MOGUL TEAM autonomous platform.
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