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Terrawarden Drone Cleanup MQP

Worcester Polytechnic Institute 2024-2025

Mark Caleca, Zephyr Conley, Jakub Jandus, Sam Markwick, Kevin Siegall, S. Taylor

Abstract

Roadside trash on highway medians causes significant environmental and economic harm in the United States. While prevention and public awareness remain the best long-term solutions, current methods of cleaning up existing litter are ineffective, dangerous, and expensive. Although ground robots have been successful at collecting trash in other conditions, the inaccessible and uneven terrain of highway medians is better suited for an autonomous aerial system. The Terrawarden drone, a one-meter-wide quadrotor with a 3-DOF manipulator and compliant gripper, addresses the problem of roadside litter by autonomously detecting and retrieving trash using on-board perception. To validate the feasibility of this approach, a controlled experiment was designed in which the drone was tasked with detecting a beverage container, navigating to it, collecting it without landing, and then transporting it to a designated collection point. The drone successfully completed each of these tasks, demonstrating the effectiveness of the proposed system and its potential for future research and deployment.

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  1. TaskManager TaskManager Public

    Python

  2. LiveDetection LiveDetection Public

    Vision stack for the terrawarden MQP

    Python

  3. DroneControl DroneControl Public

    The drone node for PX4-ROS2 communication

    Lua

  4. VisionBasedManipulation VisionBasedManipulation Public

    C++

  5. ManipulatorControl ManipulatorControl Public

    Python 2

  6. CustomMessages CustomMessages Public

    CMake

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