RBE URPS 2024

April 2024

The Department of Robotics Engineering is pleased to showcase the following Major Qualifying Project initiatives as integral components of the 2024 Undergraduate Research Project Showcase.

Table of Contents

Advancing Humanoid Robots: Demonstration of Standing and Assisted Walking Alongside a New Simulation Framework

Augmented Reality Human-Robot Interface for Assisting Robotic Manipulation

Automated Control of External Ventricular Drain for Neuro-ICU

Automated Flying Disc Inventory, v2.0

BiQu: Bimodal Quadruped Robot

BranchBot: Autonomous Quadcopter for Branch Attachment

Cube Swarm

Design and Prototyping of a Low-Cost & Efficient Ocean Cleanup Robot

Design and Assembly of a 3D Printed Humanoid Robot for At-Home Assistive Care

EVE- Agricultural Harvesting Robotic System

FASTR – Flexible Articulating Surgical Transoral Robot

HURON: Full-size Humanoid Robot (Lower Body)

Intracardiac Catheter Steering System

LEMUR: Learning and Education of Machine Learning for Undergraduate Robotics

Table of Contents

Multi-Robot Persistent Coverage Under Fuel and Stochastic Failure Constraints

Modular Hybrid Flux Motor Development for High Torque Robotics Applications

NASA Lunabotics '23-'24

Progressive Molding of Soft Robots for Ocean Conservation

SailBot 2023-24

Social Robot for Interactive Play

Soft Assistive Robotics for Helping Daily Tasks

Advancing Humanoid Robots: Demonstration of Standing and Assisted Walking Alongside a New Simulation Framework

Team Memebrs

Dylan Nguyen

Stephen Fanning

Jack Rothenberg

Scott Pena

Ana Roure

Jatin Kohli

Advisors

Pradeep

Radhakrishnan

Dirk Albrecht

Abstract

This project is a continuation of the multi-year 3Dprinted humanoid robotics MQP aiming to iterate on the simulation, electrical, and firmware solutions of previous years to create a robust, reliable, and efficient open-source humanoid robot. Ava is the current iteration of this robot. Her electrical system was updated to remove points of failure commonly found in moving wiring solutions through the development of a central circuit board and custom wires. The simulation, in CoppeliaSim, was updated to include a more accurate model of the robot along with material and mechanical properties. In simulation, Ava is now capable of unassisted standing, squatting, and walking with a cart. The real-world application of Ava utilizes high-level software through a Raspberry Pi and low-level controls through an Arduino to interact with the world. Using a 9-DOF IMU and trajectory planning with kinematics, she demonstrates walking forward while pushing a cart and standing upright independently.

Augmented Reality Human-Robot Interface for Assisting Robotic Manipulation

Team Members Advisors

Tyler Giroux

Dimitri Saliba

Justin Kyi Bryon Tom Alexander Sun

Jane Li Koksal Mus

Abstract

Robot autonomy has imprecision both in perception and action. Human assistance can correct this inaccuracy by teaching a robot to make corrective adjustments. The Microsoft HoloLens 2 is an Augmented Reality headset which allows users to view and manipulate holograms in three dimensions, which is well suited for intuitive Human Robot Interaction. However, its tracking capabilities are poorly tailored for fine robot control. Our team proposes a human robot collaborative workspace, as well as a collection of AR Human Robot Interfaces designed to facilitate human assisted robotic manipulation. In addition, we designed a compound manipulation and perception task showcasing our proposed platform to assist robot autonomy and propose a user study to evaluate its efficacy.

Automated Control of External Ventricular Drain for Neuro-ICU

Team Members Advisor

Matthew Duncan Haotian Liu

Yujie Guo Haoran Zhang

Christopher Nycz

In the complex and critical field of neurocritical care, managing patients who suffer from conditions such as traumatic brain injury (TBI), subarachnoid hemorrhage (SAH), and other related neurological disorders is a challenging endeavor. A fundamental aspect of this management involves the use of external ventricular drains (EVDs) to divert excess cerebrospinal fluid" (CSF) - a key step in alleviating the detrimental effects of these conditions. Through the management of CSF, EVDs monitor and control intracranial pressure (ICP), which is vital for the patient's recovery and for assessing the patient's neurological health. The ICP is set by physically leveling the EVD with a reference point (Kocher's point) on the patient's head. However, in the current setting, it needs frequent re-leveling due to patient movements, leading to constant intervention by hospital staff and disruption for the patient. Our project, Auto-EVD, improves the accuracy of ICP measurements and control. Our system provides real-time alerts to caregivers when changes occur, demonstrates accurate head motion tracking of targeted patients, and automatically levels the EVD. This ensures automated alignment regardless of patient movement, which minimizes staff intervention and enhances patient comfort. The device fits well into current workflows, allowing for easy integration, and provides caregivers with advanced options to deliver specific, individualized care to their patients.

Automated Flying Disc Inventory

Team Members Advisors

Benjamin Antupit

Jonathan Whooley

Daniel Ouellette

David Costa

Tristan Andrew

Matthew Adam

Claire Higginson

Greg Lewin

Walter Towner

Abstract

Maple Hill Disc Golf is a world-class disc golf organization, featuring a premier course and a reputable on-site pro-shop. To reach more customers in the community, Maple Hill intends to establish an online store; however, disc golfers traditionally prefer to purchase discs through physical examination of their features. Therefore, the team has constructed the second iteration of an automated machine that measures these features and inventories them. The machine implements modular design principles to record, maintain, and store information about each disc including the diameter, wing width, flexibility, weight, height, while also taking cosmetic photos. With this automated machine, Maple Hill aims to provide customers with comprehensive product information in order to replicate a traditional in-store shopping experience.

Bimodal Quadruped Robot (BiQu)

Team Memebrs

Ethan Chandler

Akshay Jaitly

Yifu Yuan

Puen Xu

Lehong Wang

Tao Zou

Advisors

Mahdi Agheli

Jing Xiao

Abstract

In the growing field of legged robotics, the integration of locomotion and manipulation locomanipulation poses a significant challenge, addressed by leading organizations such as Boston Dynamics, Tesla, and Unitree. This work presents an open-source framework that facilitates planning through contact, enhancing robots’ capabilities in logistics, construction, and even planetary exploration. Our approach leverages a versatile trajectory optimization method and real-time perception to generate dynamic motions, coordinated through whole-body control. We validate our framework’s effectiveness on the Unitree Go1 equipped with a custom arm, demonstrating its application across various gaits and jumping maneuvers, as well as in simulated environments on humanoid robots like HURON and Atlas. The results showcase the framework’s potential in enabling complex athletic tasks and manipulation while navigating diverse terrains.

Team Memebrs

BranchBot: Autonomous Quadcopter for Branch Attachment Advisors

Zane Altheimer

Keelan Boyle

Cooper Dean Andrew Kerekon

Andre Rosendo

Dmitry Korkin

Oren Mangoubi

Robert Krueger

Abstract

According to the United States Environmental Protection Agency, pollinators are responsible for assisting 90% of all flowering plant reproduction. However, the effects of climate change and human development have caused their habitats to decline in recent decades. Technology such as robotic bees could be used to supplement pollination efforts, but they require a mobile pollination base station. To address this, we designed a quadcopter with an underactuated grasping mechanism, custom flight software, and a depth-based vision model to identify and perch on tree branches. Our approach allows for autonomous mobile pollination in hard-to-reach locations, ensuring that natural pollinator populations have the ability to rebound.

Cube Swarm

Team Memebrs

William Albert

Phillip Brush

Benjamin Dodge

Timothy Klein

Andrew McCammon

Jason Rockmael

Dang Tran

Advisors

Gregory Lewin

Shubbhi Taneja

Reinhold Ludwig

Abstract

Current search and rescue robots suffer from being either too large to fit into tight spaces or too small to traverse terrain. To overcome this challenge, we developed a swarm of interlocking cube-shaped robots that allow robots to explore individually and traverse obstacles via coalescence. We have demonstrated our solution by using a centralized Bluetooth communication network, AprilTag localization, and an efficient path planning algorithm for our robots to explore an arena, then assemble to bridge a gap.

Design and Prototyping of a Low-Cost & Efficient Ocean Cleanup Robot

Team Members

Gabriel Espinosa

Danny Ngo

Sebastian Valle

Alexander Wadsworth

Advisors

Selcuk Guceri

Vincent Aloi

Abstract

11 million metric tons of trash enter Earth’s oceans each year, contributing to ecosystem loss, wildlife endangerment, and microplastic infiltration within the food supply. Over the past 2 decades, public awareness of the growing threat has increased, resulting in numerous organizations, like The Ocean Cleanup, seeking to curb the problem with their large-scale sweeping tugboats. However, all current efforts are costly, require large crews, and rely on diesel-powered vessels for collection and transport. Our team sought to decarbonize and automate cleanup by developing an efficient robotic platform for open ocean surface trawling. Prototypes of 2 seaworthy, inexpensive, and autonomous-capable robots were developed to tow nets for cleanup in the turbulent open ocean. The robots were designed to operate without human crews and use just 512 watts per kilogram of trash collected, 10 times less than existing systems. Future efforts may focus on commercializing the platform by selling oceanic data collected by onboard sensors.

Design and Assembly of a 3D Printed Humanoid Robot for At-Home Assistive Care

Team Members

Shivank Gupta

Anna McCusker

William Michels

Merel Sutherland

Advisors

Pradeep

Radhakrishnan

Dirk Albrecht

Derren Rosbach

Abstract

The population of U.S. residents above the age of 85 is expected to double within the next twelve years alongside the growing shortage of at-home assistive health care workers. This project aims to aid assistive care workers in performing simple at-home tasks. Finley, the humanoid robot, has been upgraded from the previous 3D printed humanoid robot MQPs and is now capable of pick-and-place and speech-to-text interaction with humans. Our open-source design also features a modular wrist connection system allowing for hands to be easily swapped without human intervention. Finley showcases this with a versatile two finger gripper which utilizes one rigid and one flexible finger. In addition, our team has redesigned Finley to reduce the number of 3D printed parts and fasteners. These changes have reduced assembly time and improved customizability for Finley. Human trust in robots was also studied to measure the perception of humanoid robots in nursing homes.

EVE - AgriculturalHarvesting Robotic System

Team Members Advisors

Soumaya El Mansouri

Lexi Krzywicki

Timothy Rinaldi

Berk Calli

Sarah Wodin-Schwartz

Yarkin Doroz

Abstract

The Eve MQP aims to minimize the time between harvest and packaging by bringing the apple grading process onto the field. Conventional methods require bringing apples into a facility after harvesting for grading, increasing time and decreasing freshness. The Eve system efficiently sorts and classifies apples based color and surface defects. Leveraging machine learning, cameras, and sensors, Eve optimizes apple production by reducing labor and reducing human error. Through collaborative efforts, the team designed, prototyped, and refined the Eve Sorting System within an academic year. By automating sorting and lessening manual labor, Eve promises heightened productivity and waste reduction, thereby setting new standards for agricultural automation.

Team Members

Chase

Beausoleil

Mark Gagliardi

Samay Govani

Cole Parks

Advisors

Loris Fichera

Stephen Bitar

Yuxiang Liu

Haichong Zhang

Yihao Zheng

Abstract

Transoral Robotic Surgery (TORS) has emerged as a promising minimally invasive approach for the treatment and removal of laryngeal tumors and lesions, offering enhanced precision and reduced clinician fatigue. Currently, the Da Vinci Single Port Surgical System is the only commercially available and FDA approved robotic system for TORS. However, the high cost, and induced remote center of motion limit the widespread adoption of the Da Vinci system. The system aims to perform TORS in the glottis region of the larynx where the workspace is constrained, and the surgical tools need to be inserted orally. This approach provides easier access by not requiring a linear insertion path for surgical tools to reach the desired location. In this paper, we present a novel robotic system for TORS that is more cost effective and less invasive than the Da Vinci system. The proposed system consists of two sub-systems: a 3-DOF robot consisting of two cylindrical tubes connected by a cable-driven flexible joint, and concentric tube continuum robots that sit inside the tubes of the 3-DOF robot. The 3-DOF robot is used to position the concentric tube continuum robots in the desired surgical workspace while the concentric tube continuum robots hold the surgical tools and provide the necessary dexterity for the surgical procedure.

HURON: Full-sized Humanoid Robot (Lower Body)

Team Members

Thai Duc Doan

Sahen Juneja

Nhi Nguyen

Carlos Giralt Ortiz

Advisors

Mahdi Agheli

Berk Calli

Markus Nemitz

Nitin Sanket

Abstract

This project builds on last year's HURON MQP, which successfully manufactured the majority of the lower body of the HURON humanoid robot. This year, we focus on improving the ankle design, building a solid open-source software platform capable of supporting any high-level research in bipedal and humanoid locomotion on HURON, and verifying our push recovery algorithm on the hardware.

Intracardiac Catheter Steering

Team Members

Megan DeSanty

Isabelle Lachaux

Elizabeth Minor

Rebecca Young

Advisors

Haichong Zhang

Shang Gao

Zhenglun Wei

Loris Fichera

Yihao Zheng

Abstract

This project aimed to reduce clinician involvement in navigating an intracardiac catheter by developing an autonomous robotic steering system. Currently, mechanically driven intracardiac catheter procedures require 2-6 hours of precise and exhausting work for a clinician. In developing this system, the team intended to alleviate the strain on clinicians, allowing them to focus on tasks that require their expertise. The robotic device encases the ICE (Intracardiac Echocardiography) catheter, and actuates the internal pull-wires using teleoperated keyboard input from the physician. This input is sent as an Arduino command to the stepper motors, which rotate the catheter knobs to provide the rotational and translational movement of the catheter tip. This movement is displayed in a real-time simulation so a clinician is able to see where the catheter is moving at all times. By providing precise control and real-time feedback, the team hopes clinicians are able to focus on more critical tasks.

LEMUR: Learning and Education of Machine Learning for Undergraduate Robotics

Team Members

Tuomas Pyorre

Ashe Andrews

Andrew McKeen

Advisors

Greg Lewin

Kevin Leahy

Matt Ahrens

Abstract

Despite an undergraduate curriculum focused on in-demand robotics topics, WPI does not offer sufficient courses for students to learn about machine learning (ML) in relation to robotics. We developed educational modules where students apply ML theory, including transfer learning, optimization techniques, and reinforcement learning to robotic systems to develop potential course material. The modules were modified into workshops for testing with students. We evaluated the modules' effectiveness by comparing students' perceived confidence and ability in select topics before and after completing a workshop. After completion, students felt more confident in their understanding of higher-level concepts in ML, but still required support to apply them.

Modular Hybrid Flux Motor Development for High Torque Robotics Applications

Team Members Advisors

Adam Blanchard

Kaeden Berry

Arturo Lemos

Andre Rosendo

Yarkin Doroz

Abstract

Motors in many high-performance robotics applications must provide high torque outputs at low duty cycles. A higher torque motor enables a more responsive actuator under load by reducing or eliminating the gear reduction in series with the motor. Due to the low duty cycle, the limiting factor in the torque output of motors in these applications is more often the magnetic saturation of the stator iron rather than the thermal properties of the motor. In this work, the authors provide a unique approach to torque optimization for this application, describe the process of designing, manufacturing, and testing a novel modular hybrid flux motor following these principles, and provide analysis and data on the torque performance of the resulting motor when compared to several common configurations.

Multi-Robot Persistent Coverage Under Fuel and Stochastic Failure Constraints

Team Members Advisor Yaşar İdikut, Camden Cummings, Samara Holmes Carlo Pinciroli

The guiding application of this research project is multi-robot systems as they relate to agricultural challenges, especially in the persistent inspection of cropland. In this research project, we present both a baseline (MILP) and novel algorithms to solve a multi-robot coverage problem under battery depletion and stochastic failures. We compare the solutions based on metrics about visitation and redundancy. Finally, we present a visualization, a simulation, and a real-world demonstration (using Khepera IV robots) setup to provide additional data to analyze our solution.

NASA Lunabotics

Team Members Advisors

Zeb Carty

Kelli Huang

Ian MacInerney

James Nguyen

Terence Tan

Sean Thal

Giovanni Giacalone

Brendan Byrne

Ken Stafford

Carlo Pinciroli

Abstract

The NASA Lunabotics competition is a robotics competition that allows teams from across the country to design and build a lunar mining robot. Teams can prove their engineering skills by showcasing a robot with the ability to navigate simulated lunar terrain, collect regolith, and construct a berm on the regolith surface. With new competition rules this year, the WPI Lunabotics Team designed and manufactured Muffin. A lightweight, agile, and autonomous robot, Muffin takes inspiration from successful robots at past Lunabotics competitions. The project also allowed the team to develop invaluable engineering skills they will use throughout their careers. Using these skills, the team developed innovative subsystems to meet the challenges of the competition.

Progressive Molding of Soft Robots for Ocean Conservation

Sara Frunzi

Dilce Oliveira

Owen Rouse

Markus Nemitz

Cem Aygül

Team Members Advisors

Abstract

Coral reefs, which house a quarter of the ocean’s biodiversity, are under threat due to plastic waste. Underwater remotely operated vehicles (ROVs) equipped with a gripper can be used to collect macroplastics caught in the reefs. Due to the frail nature of coral, these expeditions require sensitive manipulation; grippers made from soft rubbers and plastics allow for manipulation with minimal risk to the surrounding environment. However, fabrication of these grippers is often complex, time-consuming, and necessitates manual labor. We present a novel fabrication technique progressive molding to streamline the process of creating soft gripper components. By using this method, we can create complex shapes that cannot be made in a single cycle of replica molding while using materials that are too soft to be 3D printed. We design a soft gripper with actuators that can be fabricated via progressive molding. Then, we attach the gripper to a four degree-of-freedom robotic arm on a commercially available ROV to remotely clean coral reef systems. Finally, we tested our system in the WPI pool by removing macroplastics from 3D printed coral models.

Sailbot

Team Members Advisors

Mathew Gomes

Erin Murphey

Anthony Virone

Theodore Winter

Kenneth Stafford

William Michalson

Abstract

SailBot is an autonomous robotic sailboat created to compete in the International Robotic Sailing Regatta. This year’s SailBot focused on designing and manufacturing and expanding software systems. This hull was manufactured to improve water flow around the hull and increase accessibility in the SailBot for maintenance. The software systems developed focused on communications reliability, failure recovery, and autonomous functionality. Additionally, the boat's electrical system was redesigned to ensure greater platform stability and longevity.

Social Robot for Interactive Play

Joseph Baliestiero

Jayson Caissie

Kaley Du

Megan Jacques

Chloe Plasse K. (V) Valery

Team Members Advisors

Jane Li

Rose Bohrer

Social robots, which are autonomous robots with the ability to connect and communicate with humans, have become prominent in the medical and educational fields, and have even become artificial companions for people in their homes. Within the medical and educational field, social robots are used to help teach emotional and behavioral skills and help with emotional regulation. Social robots have also become commercially available, such as Jibo; a consumer-oriented robot that forms a relationship with the person or family that “adopts” it. The social robot we have developed, named Tavi, aims to connect with the person who is interacting with them via a 20-questions style game. The robot has a personality that coordinates the ear positions, arm positions, and facial expressions to convey different emotions to the user. Tavi also has facial tracking to center on the user’s face and uses a game loop to interact with the user. The game is accessible via an application that communicates with the robot, and the robot responds accordingly. Tavi is constructed mostly out of PLA and was 3D modeled using SOLIDWORKS. Tavi’s software utilizes ROS, C++, and Python to communicate with all the technology within the bot.

Soft Assistive Robotics for Helping Daily Tasks

Team Members Advisors

Luis Aldarondo

Antonios Sevastos

Ethan Weisse

Hannah Zink Berk Calli Loris Fichera Cagdas Onal

Abstract

This project focuses on creating a soft assistive robotic arm with a user-friendly interface to help people who use wheelchairs with daily tasks. This year our team created a model of this system by modifying existing origami modules, designing a soft robotic gripper, and creating a control system which integrates user inputs with sensor data to easily manipulate common household items. Soft robotics is a growing field of research. These robots offer the flexibility and adaptability that traditional rigid robotics lack, making them safer for interacting with humans and other delicate environments. This project looks at how soft robots are applicable for assistive technologies. Wheelchairs, which are used by over 3.3 million Americans, are typically used for mobility related disabilities, which often affects overall motor skills making daily tasks significantly more difficult. This design would provide greater independence to people who use wheelchairs worldwide.

SOPHT: Soft Prosthetic Hand

Christina Aube

Jeff Davis

James Doucette

Team Members Advisors

Mahdi Agheli

Markus Nemitz

Haichong Zhang

Abstract

The SOPHT project consists of a soft-layered, cable-actuated robotic hand combined with a motored-controlled arm that is anatomically proportional and accurately represents the dexterity of human capabilities. Arm functionality is demonstrated via various arm gestures and mimicking American Sign Language (ASL) gestures.

Symbiotic Multi-Agent Construction 5.0

Team Members

Genna Brown

Edward Enyedy

Can Güven

Isa Kaplan

Cambria

Pomeranz

Isabella Rosenstein

Advisors

Greg Lewin

Carlo Pinciroli

Markus Nemitz

Abstract

Robotic collective construction is an approach to automated construction that enhances safety and efficiency in the construction industry. Inspired by the observed behavior of insects, in which the construction environment acts as a shared memory for workers, this project features two types of robots: “smart” building blocks capable of storing and sending data and inchworm-inspired builder robots that navigate and modify the 3D structure. Built upon the concepts established by past iterations of this project, SMAC 5.0 improved the hardware and software design of the inchworm and the blocks, yielding a research tool for further exploration of the algorithms essential to coordinate a decentralized swarm of inchworm builders.

Trashbot: Autonomous

Trach Collecting Robot

Team Members

Matthew Sweeney

Cristobal R Rogers

Liliana Loughlin

Yuhan Wu

Advisors

Andre Rosendo

Fabricio Murai

Neil Rosenberg

Abstract

Pollution poses a significant challenge in our modern world, with humans generating vast amounts of plastic waste that endangers the environment and its wildlife. Currently, addressing this issue relies heavily on human interventions, such as clean-up efforts on roads and beaches. Unfortunately, these are typically inconsistent and unreliable. To tackle this problem, the Trashbot Major Qualifying Project at Worcester Polytechnic Institute is developing a prototype robot for the autonomous collection of plastic bottles and aluminum cans. This innovative project aims to create a robot that can navigate WPI's quadrangle independently, detect litter, approach it, collect it, and dispose of it in a designated location. The Trashbot project is a groundbreaking initiative, marking the beginning of a multiyear interdisciplinary endeavor. In the initial phase of the project, the team has achieved several milestones. They have enabled the robot to autonomously navigate using a GPS module and Inertial Measurement Unit, detect trash using a depth camera, and pass raw images to a trained object detection and classification AI model, YOLO. Additionally, the team has designed and fabricated a 4-degree-of-freedom articulated manipulator, implemented a path planning algorithm using a graph state model and installed a LiDAR fixture for future enhancements.

Underwater Filmography Using Robots

Riley Blair

Christopher Chow

Gabriel Demanche

Olivia Simon

Markus Nemitz

Carlo Pinciroli

Jeanine Denu

Dudle

Team Members Advisors

Abstract

Since its inception, cinema has utilized cutting edge technologies to bring invigorating entertainment to the masses. Despite being at the forefront of innovation, cinematographers are still limited by underwater videographers to bring their creative visions to life. After meeting with an accomplished director to define industry challenges and standards, this project utilized robotic technologies to develop an ROV capable of overcoming the unique conditions of underwater environments. Our developed product meets directors needs by safely housing a RED Komodo cinema camera while providing stable motion and framing in all 6 degrees of freedom. This harmony of robotics and cinematography introduces a novel method for underwater filmography, creating new and exciting possibilities for directors and filmmakers.

Voice Control of the HOPE Hand Exoskeleton for Individuals with Motor Impairments and Speech

Aphasia

Team Members

Connor Gaudette

Matt McGourty

Keenan

Segenchuk

Allison Rozear

Advisors

Christopher Nycz

Yunus Doğan Telliel

Haichong Zhang

Tess Meier

Erin Solovey

Abstract

The HOPE Hand exoskeleton is a motor aid for people with hypertonicity and spasticity. This project develops a voice control system for the HOPE Hand which is trained for the types of speech aphasia that often impact this patient population. Vocalizations of typical and aphasic speech were collected and used in conjunction with open source datasets for training. Existing AI models were modified and trained on these data to identify users and recognize commands, then integrated with the HOPE Hand.

Waste Sorting Robot for Recycling

Team Members Advisors

Valerie Childers

Brett Cohen Dylan

Hunt Nicholas Moy

Isaac Noble

Gabriel Ward

Lily Wolf

Berk Calli

Sarah WodinSchwartz

Abstract

With the continuous increase of yearly global waste, recycling has become an essential initiative. Despite this, issues of efficiency and profitability continue to mar efforts to expand its reach. Robotic systems offer a chance to improve and automate inadequate waste sorting processes, with recycling especially standing to benefit. This MQP represents one such solution: A conveyor belt and gantry system, designed for interchangeable end effectors, intended to operate continuously, with minimal human input by utilizing machine learning object detection.