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Autonomous Electric Lawn Mower with Modular Arm

Modular; Robots; Autonomous

Created on 2nd August 2025

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Autonomous Electric Lawn Mower with Modular Arm

Modular; Robots; Autonomous

The problem Autonomous Electric Lawn Mower with Modular Arm solves

SERGAP is designed to solve several real-world problems related to lawn and green space maintenance:

🌱 Manual labor dependency: Conventional mowing requires physical effort, which can be risky for elderly or disabled workers. SERGAP automates this task using AI navigation.

🔊 Noise pollution: Traditional gas-powered mowers generate >85dB of noise. SERGAP operates silently (<50dB), making it ideal for public spaces like parks or campuses.

🌍 Carbon emissions: Powered by solar-charged batteries, SERGAP cuts emissions by up to 75% compared to gasoline mowers.

💰 Operational costs: By reducing fuel and labor costs, organizations can save up to 60% in maintenance expenses.

🧠 Lack of adaptability: With its modular system (mower, rice planter, blower, etc.), SERGAP adapts to different use cases and seasons.

In short, SERGAP makes lawn care safer, greener, more efficient, and future-ready through autonomous technology and modular versatility.

Challenges I ran into

During development, we faced several technical and design challenges:

⚙️ Sensor fusion calibration: Integrating LiDAR, GPS-RTK, and 360° cameras into one synchronized system was tricky. Small timing offsets caused navigation errors.
Solution: We implemented a timestamp-based synchronization buffer using ROS (Robot Operating System), which aligned all sensor inputs in real-time.

🔋 Power management: Balancing power supply between motors, sensors, and compute units while ensuring battery efficiency was complex.
Solution: We optimized the motor PWM control and used solar panels as supplementary charging during idle periods.

🌧️ Environmental safety: The robot needed to detect rain and slippery conditions autonomously to avoid malfunction.
Solution: We added humidity and rain sensors with an auto-return-to-base protocol if adverse weather is detected.

These hurdles taught us the importance of iterative prototyping, system-level debugging, and designing with real-world unpredictability in mind.

Technologies used

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