Agricultural Pest Deterrent Robot

An autonomous mobile robot designed for non-lethal deterrence of crop-damaging wildlife, targeting real-world deployment in agricultural settings.

Overview

This project addresses a practical agricultural problem: the damage caused by wildlife — particularly monkeys and wild boars — to crops in semi-rural and rural farming areas. The proposed solution is an autonomous or semi-autonomous mobile robot platform capable of detecting and deterring intruding animals using non-lethal means.

The project is framed as a capstone-ready engineering problem, balancing practicality, cost, and field robustness as primary design constraints.


System Concept

The robot operates as a mobile deterrent unit, patrolling defined agricultural zones and responding to detected intrusions automatically.

Detection

  • Vision-based or sensor-based motion detection
  • Configurable sensitivity and detection zones

Autonomous Behaviour

  • Scheduled or reactive patrol routines
  • Boundary-aware navigation within defined field areas

Deterrence Mechanisms

  • Sound-based deterrence (alarm, distress calls)
  • Light-based deterrence (flashing or directed illumination)
  • Motion-based deterrence (movement towards intruder)

All deterrence mechanisms are non-lethal and designed to condition animals to avoid the protected area over time.


Design Constraints

The system is designed with field deployment realities in mind:

  • Low cost — suitable for smallholder and community farm adoption
  • Robustness — operational in outdoor, unstructured environments
  • Maintainability — accessible to non-specialist operators
  • Energy efficiency — compatible with solar or battery-based power where mains is unavailable

Engineering Significance

This project sits at the intersection of autonomous systems, agricultural technology, and human-robot interaction in real-world settings. It provides a meaningful engineering challenge that requires integrating perception, navigation, and actuation within tight cost and robustness constraints — making it an effective vehicle for applied robotics education and research.