Sumo 3K - Post 06 - Results & Future

This final post discusses testing outcomes, weight verification, and the servo lever torque calculation for the planned enhancement.


















With the chassis built, electronics wired, and firmware uploaded, the first full integrated test was the moment of truth. The robot connected to the phone over WiFi immediately — the web interface loaded, and the first tap of the forward button drove all four wheels in unison. That moment felt genuinely satisfying after weeks of work.


All five movement commands were verified: forward, backward, left turn, right turn, and stop. The turning radius was tight enough for the 1.5-metre arena — the robot could pivot on the spot by driving the left and right wheel pairs in opposite directions.


One issue appeared: after fitting the top chassis cover, the robot wouldn't move from standstill without a small initial push. Root cause: battery voltage had depleted slightly during development, and the added weight of the cover increased static friction. Charging the battery resolved it: confirming that μs > μk in a very tangible way.


Final verification

Final weight - 2.35 kg

Weight headroom - 650 g

Drive modes - 5 verified

Award - CREST Gold


What comes next: the servo lever

The 650 g of weight headroom opens up the most impactful planned enhancement: a front-mounted lever driven by a metal gear servo motor. The lever's purpose is to slide underneath the opponent and lift their front wheels, reducing their traction by transferring some of their weight onto the lever arm. Mechanically, this cuts their effective pushing force significantly.


The maximum lever length can be calculated from the servo's torque rating and the maximum opponent weight (3 kg × 9.81 m/s² = 29.4 N):


Lever length calculation

L_max = τ_servo ÷ W_opponent


For a 20 kg·cm (1.96 N·m) servo: L_max = 1.96 ÷ 29.4 ≈ 6.7 cm

A metal gear servo (typically 60–90 g) fits comfortably within the 650 g headroom.


Sensor integration roadmap

A further future version could incorporate IR or ultrasonic sensors to detect the arena boundary and opponent position, enabling semi-autonomous behaviour — the robot could detect the edge of the arena and automatically turn before falling out, or detect the opponent's approach and respond without human input.

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