An interactive opportunity for faculty judges, fellow students, and outside guests to listen to, learn from, and appreciate the work of our 2022 Major Qualifying Projects.
Friday, April 22nd Schedule
Professor Jing Xiao, Head, Robotics Engineering Department
MQP 1 - Multi-Robot SLAM
Methods of swarm SLAM are becoming increasingly prevalent in academic literature. So far, the bulk of research in SLAM has focused on single-robot or centralized SLAM approaches. These systems are capable of producing accurate maps but miss the opportunities for parallelism and robustness offered by swarm robotic systems. In this work, we present an end-to-end solution for decentralized map synchronization with occupancy grids for swarm robotic systems. The algorithms presented are packaged in a ROS node alongside a custom communication network to facilitate inter-robot map merges.
Team Members: Tyler Ferrara, Peter Nikopoulos and Connor McLaughlin
Advisors: Professor Carlo Pinciroli
MQP 2 - Beach Swarm
The issue of beach pollution is continuously growing and negatively affects both human and marine health. While there are currently several methods of beach clean-ups, many are done by hand and often overlook small litter such as cigarette butts. The goal of this project is to design and build an autonomous robot that can clear beaches of harmful litter. To achieve this, the team redesigned the previous robot to be more inclusive of smaller, more common forms of beach litter. This robot expands on current robotic beach-cleaning efforts and provides a scalable solution for future implementations of a multi-robot, swarm-like approach.
Team Members: Samuel Bello, Lauren Sowerbutts, James Casella, and Matthew Langkamp
Advisors: Professors Nicholas Bertozzi and Bradley Miller
MQP 3 - Escape Room Robotics
The versatile nature of escape room games allows for the creation of a physical environment to be played virtually by a robot, enabling the disciplines of game design and robotics engineering to intersect. The overall goal of this Major Qualifying Project was to create a framework for the creation of these robotic escape rooms, determining the methods needed to form a compelling, modular environment and design a teleoperated robot with distinct functionalities to operate within that environment. Using this framework, the team created one such iteration of a miniature robot escape room, wherein the player remotely interacts in real-time with obstacles in the actuated room, facilitated by computer vision techniques and peripherals on the robot itself.
Team Members: Owen Buckingham, Edward Matava, Alyssa Moore, and Matthew Nagy
Advisors: Professors Berk Calli and Gillian Smith
MQP 4 - Augmented Reality for Ultrasound Imaging
Ultrasound imaging is a widely used method to painlessly visualize internal structures of the human body through the propagation and reflection of inaudible sound waves. Due to the relative complexity of an ultrasound procedure, it takes a considerable amount of training to achieve accurate results. To get even a simple reading, a Sonographer, (medical imaging professional) requires a year or two of education to become qualified to gather these images. In an effort to minimize required training and lower the bar of entry for the operation of an ultrasound probe, a team of WPI students aimed to utilize Augmented Reality (AR) to improve the ultrasound operation experience. The goal of this project was to use the Microsoft Hololens 2 AR headset to display the ultrasound images gathered by a Clarius portable ultrasound probe in real time on the patient’s respective anatomy. The students were able to access the ultrasound images and position data in real time and load them both into the Microsoft Hololens 2. However, due to networking issues and time constraints, the team was unable to load both the ultrasound and position data into the Microsoft Hololens 2 simultaneously. With further research into the communication problem, the team is confident that this is a valuable and feasible solution to minimizing ultrasound training.
Team Members: Mary Barsoum, Sarah Lombardi, and Ian Scott
Advisors: Professors Yihao Zheng and Haichong Zhang
MQP 5 - Bio-inspired Exosuit
Conventional artificial limbs, braces, and related technologies designed to assist users who are unable to produce a normal walking (gait) cycle have a variety of factors that limit their applicability to people of various body types. By attaching soft, pneumatically-actuated artificial muscles (“Hydro Muscles”) to a flexible undersuit, assistive devices can be produced to lower the physical exertion necessary to walk. This project continues on a multi-year effort to utilize Hydro Muscles for this purpose. Specifically, the introduction of neural network-based control, informed by a comprehensive suite of orientation, position, and force sensors, enables this assistive device (“Bio-Inspired Exo-Suit”) to adapt to the user’s gait cycle and provide directed support to decrease the energy consumed in a significant manner.
Team Members: Peter Buterbaugh, Lily Durkin, Haojun Feng, Yichen Guo, and William Shaver
Advisors: Professors Marko Popovic and Ziming Zhang
MQP 6 - NASA Extreme Terrain Mobility
Capstans have been used for centuries on ships in order to assist with moving heavy loads that could not have otherwise been lifted. To capitalize on this idea and the capstan equation, a mechanism can be created in such a way that it can engage an unpowered shaft with a prime mover similar to some sort of transmission. The benefits of this design allow for a light weight controllable system that has a variety of applications ranging from that of a moon rover or boat to even cars and other terrestrial vehicles. In order to test this theory a rig was mocked up that would allow for tension control of a rope that would use friction to engage two different shafts, and the data that was collected from this will help highlight the benefits and downsides of an application similar to this. Not only would this be testing general characteristics, but also the materials used and how they would change the system as a whole, such as rope materials, the coefficient of friction and amount of loops on each shaft.
Team Members: Stephen Chavez and Kathryn Stoval
Advisors: Professor Marko Popovic
MQP 7 - Design of Mobile Robotic Base
Mobile robotic bases provide mobility for robotic serial manipulators and are essential for service technologies, warehouse applications, and robotics research. However, current mobile bases are expensive and require significant effort to integrate with robotic manipulators. The goal of this MQP was to design and implement a modular, programmable, and affordable mobile platform for interfacing with various manipulators. The team created a chassis and elevator system to increase mobility and introduce effortless electrical and mechanical integration with various manipulators utilizing a modular design. Furthermore, abstraction between user input and manipulator-specific hardware drivers was developed for seamless control of the base and manipulator.
Team Members: Kenneth Armijo, Alexander Corey, Braden Foley, Edward Jackson, and Timothy McCarthy
Advisors: Professors Berk Calli and William Michalson
MQP 8 - DigSafe Auto Cable Detection System
Dig Safe regulations require utility companies to mark the location of buried utilities prior to the start of a construction project. Detecting and marking cables is time consuming, monotonous, and can be dangerous to utility workers due to the working environment. The goal of this project is to develop a semiautonomous robotic system that detects and marks buried electrical cables safely and efficiently. The robot manipulates an industry-standard utility locator to find buried electrical cables. Standard utility markings are spray painted on the ground above these electrical lines using a two degree of freedom arm. GPS and LiDAR sensors are used to localize the robot within its environment. The robotic prototype is capable of detecting and following a cable in a straight line, marking the cable using spray paint, and navigating a controlled environment containing static obstacles such as curbs and streetlights.
Team Members: Brigid Auclair, Casey Gosselin, Amber Lindberg, and Kyle Mitchell
Advisors: Professors Greg Lewin and Jing Xiao
MQP 9 - A Hopping Two-Wheeled Segway Robot
Our team took a commercial Segway and modified it to be driven autonomously as well as support a jumping mechanism. The Segway was retrofitted with a new microcontroller and motor drivers. A simplified physics model was created for simulation of the working configuration of the robot, while the jumping mechanism was designed and manufactured. The final Segway is capable of autonomous balancing with support for the jumping mechanism."
Team Members: Christian Defranco, Samuel Mwangi and Russell DeSouza
Advisors: Professor Siavash Farzan
|10:30 AM||Break - Poster Presentations|
MQP 10 - 6 Axis 3D Printer
Additive manufacturing and rapid prototyping is a major factor in modern industry. The goal of the 6-Axis 3-D printer project is to create a hardware and software platform for performing mobile 6-axis additive manufacturing on a hexapod base. The 6-axis 3-D printer translates in the x-, y-, and z-axes and rotates in the a-, b-, and c-axes. Being 6-axis removes the need for supports to be printed, speeding up print times. Being a mobile 3-D printer allows for a theoretically infinite print area/size of the print. The software converted 3-D models into 6-axis instructions for the robot without further user input.
Team Members: Caden Crist, Christopher Cook and James Krigsman,
Advisors: Professors Michael Gennert and Mohammad Mahdi Agheli Hajiabadi
MQP 11 - Robotics for Recycling Industry
At both a nationwide and residential level, modifications to education and sorting practices in the recycling industry have had a huge impact on how much material is being recycled. Research into best practices in recycling shows that counties and cities with high percentages of material recycled have a heavy focus on sorting. As such our project, Robotic Recycling Recovery (RRR), seeks to further refine and optimize the way places like Massachusetts sort their waste. We designed an autonomous system which is capable of detecting and removing recycled materials from a conveyor belt through the use of deep learning object localization and classification as well as a bi-directional arm with pneumatic suction cups. We also created our own dataset to train our deep learning model and a user interface to correct it during operation. RRR specifically aids in the separation of cardboard from other types of waste to assist material recovery facilities’ ability to separate waste so it can be recycled.
Team Member: Nathan Bargman, Kaitlyn Fichtner, Mary Marquette, Garett Ruping, Conrad Tulig, and Lauren Wach
Advisors: Professors Berk Calli, Jennifer Rudolph and Sarah Jane Wodin-Schwartz
MQP 12 - Solar Agribots
As populations rise and the agriculture industry takes on more demand for crop yields, farmers find themselves strained. The insertion of robotics and autonomous technology into farming is a solution that supplements the work and exertion of the farmers. The purpose of this project is to combine drivetrain technology, a base station, water deployment hardware, and autonomy into an individual robot that makes up the unit of a swarm designed to navigate and irrigate crop fields while being independent and reliable on solar capabilities. The robot is to be replicable into as many units desired by the owner depending on the size of the farm and crop fields.
Team Members: John Benoit, Raymond Carter, Nicholas Hudgins, Stephen Kendrish, Nathan Maldonado, Sam Ng, John Pattison, Calvin Thomas, and Calvin Zhang
Advisors: Professors Kaveh Pahlavan, Mehul Bhatia, and Nicholas Bertozzi
MQP 13 - Wildland Firefighting Robots
With the increasing scale of wildfires across the western United States, robots can fill the gap in manpower needed to combat these fires. The goal of this project is to design and build a scaled-robot that will lay the groundwork in effective and autonomous indirect fireline robotic construction. The robot will be driven by teleoperation or by autonomously following flags. In order to adjust the plow position, two separate subsystems have been developed to control the plow horizontally and vertically. The robot must be able to traverse terrain safely and efficiently, as well as provide methods to simulate the removal of flammable material on the ground to expose the mineral soil.
Team Members: Anna Eng, Nigel Kobayashi, Andy Li, and Trang Pham
Advisors: Professors Albert Simeoni, Carlo Pinciroli, and James Urban
MQP 14 - Electronic Exoskeletal Hand
The aim of Electronically Controlled Exoskeletal Hand (ECEH) is to create a wirelessly controlled robotic hand that is actuated with a wearable exoskeletal controller that easily fits to a user’s hand. The controller provides the user with haptic feedback that simulates the force the robotic hand encounters when grabbing an object. The team worked to create a functional wireless hand and controller at a fraction of the cost of similarly functioning robotic hands on the market. This system was designed to maintain a high level of functionality and precision, as well as incorporate extra capabilities like haptic feedback, wireless functionality, and real-time control. ECEH’s goal is to bridge the gap of the industrialized robotic hand and end of arm tool (EOAT) market and general consumer through pricepoint and capability.
Team Member: Matthew Rothman
Advisors: Professors Gregory Fischer and Mohammad Mahdi Agheli Hajiabadi
MQP 15 - SMAC (RAINSTORM)
Roofing is one of the most dangerous construction jobs, accounting for nearly 20% of total construction workplace fatalities in 2019. Autonomous robotic construction can increase worker safety and the overall workplace efficiency. However, these technologies are often designed for a single project and are not scalable. Therefore, we are applying an inchworm robot platform to shingle a roof with custom data shingles. Our system is a decentralized swarm of inchworm robots designed to collaboratively shingle roofs. These robots are able to communicate and collaborate by storing data within placed shingles. Overall, the use of a decentralized swarm that communicates through the environment will prevent single points of failures and increase reliability.
Team Members: Elias Benevedes, Dominic Ferro, Samantha Gould, and Filip Kernan,
Advisors: Professors Carlo Pinciroli, Greg Lewin, and Markus Nemitz
MQP 16 - Electric Snowboard
Snowboarding is a popular sport and recreational activity in the wintertime. Unlike cross country skiing, snowboarding is limited to riding on downhill terrain. This limitation of traditional snowboards and the popularity of electric skateboards inspired the Glacier Glider, an electric snowboard capable of traversing over snowy flat ground and slight hills. The board is propelled with a tread system attached to an adjustable suspension mechanism which can accommodate various snow conditions. Much like an electric skateboard, the device is powered by a rechargeable battery and controlled with a handheld remote. To ensure rider safety, the device includes a notification system to warn the user of low battery levels, a blocked drive system or otherwise unsafe condition. The device’s safety shield adds another layer of protection, which acts as a sled for downhill snowboarding.
Team Members: James Englander, Nicholas Franzini, David Smith, and Erin Thibeault
Advisors: Professors Kenneth Stafford and William Michalson
MQP 17 - Stair Capable Vacuum
The commercial robotic vacuum is unable to bridge the coverage gaps associated with having multiple levels in a home. Staircases are insurmountable and uncleanable environments to these devices and divide a household into isolated regions. This project proposes a robotic vacuum platform that can unite these regions by traversing and cleaning stairs while maintaining a form factor practical for cleaning the rest of the home. The novel design features a three-stage platform interconnected with scissor lifts, which allows the robot to control its center of gravity and vertically extend to the heights required for stair climbing while retaining a retracted height less than that of a single stair. In tandem with the omnidirectional drive system, sensing capabilities, and wall-following control algorithm, this platform can traverse an entire multilevel home.
Team Members: Benjamin Draper and Sawyer Wofford
Advisors: Professors Siavash Farzan and Jing Xiao
MQP 18 - 3D Humanoid Robot
Robotic research on humanoid robots often involves expensive hardware. Using modern manufacturing techniques and off the shelf components a small humanoid robot can demonstrate many of the capabilities of larger systems at a lower price point. We present a 27 degree of freedom humanoid robot based on the Poppy Project. The robot operates untethered using internal battery power and an onboard Raspberry Pi and manipulates objects up to 100 grams with grasping hands. We demonstrate this functionality using a record/play system that allows a human operator to manually position the robot and then record those positions for later playback.
Team Members: Raymond Beazley, William Engdahl, Anthony Galgano, David Fournet, and Alexandria Lehman
Advisors: Professors Pradeep Radhakrishnan and Kaveh Pahlavan
MQP 19 - CLARA – Continuum Locomotion Alternative for Robotic Adaptive Exploration
Current forms of remote pipe inspection, such as borescopes, are limited in their maneuverability. We propose a salamander inspired soft robot as a novel pipe inspection tool that can overcome many pipe sizes, vertical pipes, tees, and bends using a variable diameter suspension mechanism. The origami body uses a Yoshimura crease pattern to create deformable cable driven bellows, enabling steering without traditional rigid mechanisms. To enable closed-loop position and velocity control, we introduce a smart motor driver PCB, useful for applications beyond this project’s scope. They communicate over I2C by a custom mainboard receiving remote commands via WiFi and UART from gamepad input. The system achieves 4.5” of linear compression, 1.6” of diameter range and 85.8° maximum bending angle.
Team Members: Brian Katz and Katelyn Wheeler
Advisors: Professor Cagdas Onal
MQP 20 - NASA Lunabotics
The goal of this project is to build a semi-autonomous lunar mining robot for the 2022 NASA Lunabotics Competition. As NASA carries out the Artemis program, the Lunabotics robots act as prototypes for autonomous sample collection rovers for lunar exploration. The robot is designed to autonomously navigate rough terrain, mine icy regolith simulant, and deposit regolith into a collection sieve. At the conclusion of the project, the majority of the performance metrics were met by the robot. The social implication of this project allows for a growing number of students and future engineers to learn and apply systems engineering skills through the Lunabotics challenge, which prepares them for industries that rely on these principles.
Team Members: Jesulona Akinyele, Manjusha Chava, Payton Grant, Corinne Hartman, Karen Hou, Nikita Jagdish, Tyreese James, Sarah McCarthy, Nathan Ng, Jacob Parker, Michael Rosetti, Julia Sheats, Thomas Sterrett, and Jacob Yurcak,
Advisors: Professors Kenneth Stafford, Joshua Cuneo, Yorkin Doroz, Therese Smith, and Walter Towner
MQP 21 - Design Novel Colonoscopy Probe
Detection and identification of polyps during regular colonoscopy screening are crucial in the treatment and prevention of colorectal cancer. However, the current standard white light colonoscopy and biopsy have limitations in detecting and identifying polyps. The objective of this study is to develop a colonoscopy probe that can identify the polyps at the time of screening by electrical measurements. It has been shown that the electrical impedance of polyps decreases as a function of neoplastic progression. Our proposed probe is based on a snare tool that can fit within an instrument channel of a conventional colonoscopy probe with embedded electrodes to enable electrical impedance measurements. We detail the design, prototyping, and initial experiments with simulated polyps. Our results indicate that our device has the ability to identify cancerous and healthy tissue. This tool could help colonoscopy practitioners with polyp identification by measuring the bioelectrical properties of the polyp tissue in situ.
Team Members: Mary Decelles and Hannah Lindsey
Advisors: Professors Ahmet Sabuncu and Cagdas Onal
|BREAK - Poster Presentations|
MQP 22 - Origami (OREO'd)
The demining of landmines using drones is challenging; air-releasable payloads are typically non-intelligent (e.g., water balloons or explosives) and deploying them at even low altitudes (~6 meter) is inherently inaccurate due to complex deployment trajectories and constrained visual awareness by the drone pilot. Soft robotics offers a unique approach for aerial demining, namely due to the robust, low-cost, and lightweight designs of soft robots. Instead of non-intelligent payloads, here, we propose the use of air-releasable soft robots for demining. We developed a full system consisting of an unmanned aerial vehicle retrofitted to a soft robot carrier including a custom-made deployment mechanism, and an airreleasable, lightweight, and untethered soft hybrid robots with integrated electronics that incorporate various pneumatic actuators. We demonstrate a deployment cycle in which the drone drops the soft robotic hybrid from an altitude of 4.5 m meters and after which the robot approaches a dummy landmine. By deploying soft robots at points of interest, we can transition soft robotic technologies from the laboratory to real-world environments.
Team Members: Archie Milligan, Tyler Looney, and Danield Perno, Nathan Savard, Michael Scalise, Augustus Teran, and Ryley Wheelock,
Advisors: Professors Cagdas Onal, Carlo Pinciroli, and Markus Nemitz
MQP 23 - Autism, Anxiety Assist Robots (PABI)
The goal of this project was to combine engineering and psychology to modify a socially assistive robot (SAR) to more effectively assist children with autism spectrum disorder (ASD) in practicing behavioral therapy. Children with ASD frequently struggle with anxiety, so integrating mindfulness activities into the robot’s online therapy system allows the user to develop social skills and emotional regulation techniques more successfully. For this iteration of the Penguin for Autism Behavioral Intervention (PABI) robot, we implemented guided mindfulness practices for when the user exhibits stress-related emotions during their behavioral therapy and expanded the robot’s existing behavioral learning activities. Our modifications enable the PABI robot to guide the user through mindfulness activities both verbally with a text-to-speech module and physically with a mechanical system that mimics human breathing. We also created and tested an algorithm that determines whether the user is experiencing stress or anxiety based on their facial expressions. If the algorithm detects stress-related emotions during a therapy session, the robot will suggest a mindfulness exercise for the user to complete to help them refocus on their behavioral therapy. To supplement our modifications, we conducted an experimental study with 36 undergraduate students to test the effectiveness of the PABI robot’s guided mindfulness practices in decreasing participants’ stress levels.
Team Members: Jennifer Lewitzky, Erin Perry, and Elizabeth Roberts
Advisors: Professors Gregory Fischer, Jeanine Skorinko, and Kevin Lewis
MQP 24 - Simulation of Nursing Robot Tasks
The current 3d dynamic simulators with the ability to efficiently simulate robots in complex indoor and outdoor environments like Gazebo-3d have shortcomings like inadequate physics engine, unrealistic force measurements and poor real time factor. This project aims to develop a ROS- and Unity-based simulation of a mobile manipulator robot performing various nursing assistance tasks in a simulation environment. The simulation robot modal, tasks and scenarios are designed to evaluate the capability of tele-nursing interfaces to control the nursing robot for dexterous navigation, manipulation, loco-manipulation and physical human-robot interaction. Through testing robot models like Double3, Gopher, Gopher Presence, Freight base and Kinova Robotic Arm; and sensor packages like Laser scan and RGB-D Camera, we deduce that simulations in Unity are more detailed and closer to reality than the simulations in Gazebo.
Team Members: Kushal Gandhi
Advisors: Professor Jane Li
MQP 25 - On-Campus Delivery Robot
The demand for robotic deliveries has increased exponentially under the mandates of social distancing because it provides contactless services. We designed an autonomous delivery robot for the WPI campus, capable of transporting packages, food, equipment, and other items from one location to another. To successfully complete deliveries, the robot drives on a novel inverse belt box transmission system and navigates using path finding, path following, and collision avoidance.
Team Members: Lucas Buermeyer, Tian Yu Fan, and Nicholas Hom
Advisors: Professors Bradley Miller, Michael Engling, and Nicholas Bertozzi
MQP 26 - Metamorphic Manufacturing
Metamorphic manufacturing is a type of digital fabrication wherein robotic systems are employed to incrementally deform material into the desired shape. This approach has the potential to reduce material waste compared to subtractive methods such as CNC milling and can achieve material properties superior to what is possible with additive methods like 3D printing. The aim of this project is to develop a prototype metamorphic manufacturing system capable of shaping plasticine clay. Utilizing the 6-axis ABB IRB 1600 robotic arm equipped with a custom end-effector and interchangeable tools, a system was constructed to achieve this objective. A LiDAR camera was explored to capture accurate 3D models of the Plasticine workpiece as it is being shaped. Automated tool-changing was also explored to allow for a fully automatic workflow.
Team Members: Patrick Siegler
Advisors: Professors Adam Powell, Berk Calli, Craig Putnam, and Sniha Narra
MQP 27 - Lionfish Harvesting Robot – Phase V
Lionfish, a species of venomous fish indigenous to the Indo-Pacific Ocean, are an invasive species along the southeast coast of the United States and the Gulf of Mexico. Due to the absence of any natural predators, their exponential rate of reproduction, and their ability to survive in a wide range of habitats, their population has been growing rapidly in the Atlantic Ocean. As a result, they are destroying the coral reefs and fish that live in and around the reefs, thus damaging the local ecosystem. The Lionfish MQP aims to mitigate the spread of the lionfish population by creating a remotely operated vehicle (ROV) to harvest lionfish. This year’s team plans on expanding and improving the work done by the previous iterations of this project. The team’s focus is to design and implement new spearing design, employ machine learning and computer vision to detect lionfish, and implement autonomous underwater navigation.
Team Members: Owen Blaufuss, Kathleen Cochran, Atharva Dikshit, Julia Meisser, Justin Mitchell, and Brandon Snapperman
Advisors: Professors Bradley Miller, Craig Putnam, and William Michalson
MQP 28 - Partial Hand Prosthetic: Core Function
The lack of partial hand prosthetics for amputations at the metacarpophalangeal joint has necessitated the development of a solution that bridges this gap in prosthetic technology. This is addressed via a case study involving a patient with an amputation at the metacarpophalangeal joint of their index finger and nearly complete amputation of the proximal phalanx of the thumb. The resulting solution consists of a servo-driven artificial thumb controlled by motion in the residual bone fragment of the patient’s biological thumb, and a passively actuated index finger controlled by the motion of the patient’s middle finger, with special focus on form factor, mechanical simplification, and improving on various shortcomings of the previous versions. Qualitative and quantitative testing indicates that the prosthetic restores several manual capabilities to the amputee.
Team Members: Liam Benjamin, Adele Burton and Ander Carbajo Perez
Advisors: Professor Marko Popovic
MQP 29 - Partial Hand Prosthetic: Experimental Features
Most partial hand prosthetics made today are non-functional, providing aesthetics rather than dexterity. Prosthetics that provide dexterity are only available for either full hand amputations, or for finger amputations with a remaining proximal phalanx. The purpose of this project is to fill that gap. This MQP worked in conjunction with the Partial Hand Prosthetic: Core Function MQP to expand upon last year’s Partial Hand Prosthetic MQP to integrate haptic feedback systems, allow for variable compression, and enhance thumb control. To continue to improve the partial hand prosthetic design we created a web interface allowing customization of the prosthetic’s behavior, sensors determining compression on the prosthetic fingers to control vibro haptic feedback to the user, a harness which the user can control the tightness of, and increased thumb positioning accuracy via an array of hall effect sensors. Through qualitative and quantitative testing, the device has demonstrated its ability to give feedback while restoring dexterity.
Team Members: Nicole Dressler, Brian Fay, Andrew Fisher, and Luke Reid
Advisors: Professors Gregory Fischer, Joshua Cuneo, and Marko Popovic
MQP 30 - Sailbot
The goal of this project is to improve upon prior iterations of SailBot, an autonomous robotic sailboat. This was accomplished by improving the mechanical, electrical, and software systems already in place, as well as adding new systems. Our overall objective for this iteration is to increase the rigidity and reliability of the vehicle.
Team Members: Andrew Del Velcchio, Renee Gruner-Mitchell, Deep Kumar, Tom Nurse, Jieyuan Song, Molly Sykes, Anthony Tesriero, and Jarius Thomas
Advisors: Professors William Michalson and Kenneth Stafford
MQP 31 - FSAE Electric Car
Formula SAE Hybrid Competition is an annual design and engineering collegiate challenge. The goal of this year’s FSAE team was to design, build, and compete with a formula-style electric, open-wheel racecar. This project brought together an interdisciplinary team of 21 students from ME, ECE, RBE, and CS. Despite the constraints, which included: competition rules, finances and time required to complete the race car, our team members conceived and manufactured several components: drivetrain, suspension, custom battery, tractive system components and braking to satisfy design requirements and structural FEA. Additionally, various circuits were designed and built to meet the rules, including shutdown, pre-charge and discharge, brake system plausibility, tractive system active light, an electric vehicle control unit and additional printed circuit boards for optimization and testing. We worked on the integration of the mechanical systems with the electrical systems to obtain a fully operational racecar.
Team Members: Andreas Akesson, Jessica Babcock, William Burnham, Gabriel Dudlicek, Jorgo Gushi, Alexandra Heline, Nicholas Karatzas, Aditya Kumar, Giahuy Lenguyen, Nicolas Machado, Anthony Macrina, Austin Master, Nicholas Panzardi, Kevin Ramos, Alexander Rivera, Ilyas Salhi, Shawn Salvatto, Molly Steinberg
Advisors: Professors William Michalson and David Planchard
MQP 32 - Bot on a Wire
Large numbers of cormorants perch on a Eversource Energy power distribution line over Cedar pond (Cape Cod, MA) after hunting in order to dry their wings. While perching, they defecate into the water below, altering the water’s chemistry such that it kills fish and causes other environmental issues. Additionally, cormorants are a loud bird species, and they disturb the residents in the vicinity of cormorants’ roosting locations. The goal of this project is to create an inexpensive, automated solution to deter cormorants from landing on the powerlines. This project aimed to design and test a prototype solution that can be field-tested. The robot developed during the project can traverse a power cable, detect a bird using ultrasonic sensor, switch on sound and light deterrent, and charge itself through a docking station.
Team Members: Kohmei Kadoya
Advisors: Professor Greg Lewin
Professor Greg Lewin, Associate Head, Robotics Engineering Department