Matt DeDonato| Manager, Vehicle Hardware Group

Personal information

Location Cambridge, Massachusetts
Currently working Toyota Research Institute
Matt DeDonato


  • 2012 - 2013

    Masters of Science in Robotic Engineering
    Worcester Polytechnic Institute

    • Capstone Project – NASA Sample Return Robot Challenge: Spring 2013
         - Developed vision-based sample recognition and retrieval for autonomous rovers
         - Assisted in managing 5 robotics engineers to complete the project
  • 2005 - 2009

    Bachelor of Science in Robotic Engineering
    Worcester Polytechnic Institute

    • Interactive Qualifying Project–Science Museum London: Summer 2007
         - Adapted exhibits to be accessible to the visually impaired
    • Major Qualifying Project–Modular Robotics Platform: Summer 2008
         - Designed and constructed educational robotics platform
  • 2001 - 2005

    Pomperaug High School


  • Apr 2016 - Present

    Manager, Vehicle Hardware Group
    Toyota Research Institute

  • Sep 2015 - April 2016

    Senior Robotics Software Engineer
    HStar Technologies

    • Developed system architecture for new automated patient lifting device
    • Developing embedded firmware and control software for automated patient lifting device
    • Took on project management role for electrical and software systems
  • Nov 2015 - Jun 2017

    Independent Contractor
    Woods Hole Oceanographic Institution (JPAnalytics)

    • Developing firmware for new underwater communication board
  • Jul 2015 - Sep 2015

    Senior Software Engineer
    QinetiQ North America

    • Created arm collision avoidance algorithm for fourth generation talon robot
    • Upgraded user interface PHP site for power line monitoring system
  • Aug 2013 - Jul 2015

    Technical Project Manager & Senior Robotics Engineer
    DARPA Robotics Challenge, Team WPI-CMU

    • Assembled and managed a team of 25-30 engineers to compete in the DARPA Robotics Challenge
    • Lead the team in developing the robot to drive a car, traverse terrain, turn valves and much more
    • Awarded $2.5 million in funding and over $2 million in equipment
    • Placed among top teams at the DARPA Robotics Challenge Trials and Finals
  • Jun 2013 - Jul 2013

    Research Assistant
    Worcester Polytechnic Institute

    • Development of a Robotic-Augmented Electronic Baggage Screening System for Airports
  • Jan 2013 - Jun 2013

    Teaching Assistant
    Worcester Polytechnic Institute

  • May 2010 - Aug 2012

    Embedded Systems Engineer
    Teledyne Webb Research

    • Worked to maintain and improve software for APEX float line
    • Worked with clients to develop custom platforms based on their specific needs
    • Designed and implemented next generation control boards and software for APEX float line
    • Contributed to development of new products and expanding features of current products
  • Jun 2009 - May 2010

    Robotics Engineer
    DeepQuest, LLC

    • Designed electrical systems for underwater robots
    • Designed, built and programmed embedded circuit boards to control robotic subsystems
    • Developed software for testing and control of embedded circuit boards
    • Setup and maintained network server for remote access and data storage
  • Apr 2004 - Dec 2007

    Senior Intern
    Nexus Design, LLC

    • Responsible for bringing a product from concept into production.
    • Extensively used SolidWorks along with many other design programs.
    • Maintained FTP site, phone systems, network systems and computers.



    The NASA Sample Return Robot Challenge is an autonomous robot challenge geared at develping technologies for use on space rovers. The challenge requires the demonstration of an autonomous robotic system that can navicate a large open field to locate and collect a set of specific sample types. The field area includes open rolling terrain, granular medium, soft soils, and a variety of rocks, and immovable obstacles. For more information on the challenge visit


Team AERO strives to foster a dedicated and collaborative team, composed of graduate and undergraduate students, to develop and implement innovative open-source control, navigation, perception, and manipulation algorithms enabling robots and humans to reach further into space. We aim to demonstrate successful autonomous collection of geologic samples of interest utilizing AERO with the intent of gaining experience in the holistic system design process, improving our robotics engineering skills, and building an inovative new robot. For more information on the team visit


We posit that despite the significant automation currently employed by the TSA in the Checked Baggage Inspection Systems (CBIS), the addition of innovative robotic technologies in the baggage screening process can significantly reduce the labor-intensive tasks required to manually inspect some bags. Technologies enabling robots to work in close collaboration with humans can address issues in implementing Electronic Baggage Screening Program (EBSP) strategic plan goals. For example, the labor-intensive explosives trace detection (ETD), where a piece of fabric is swabbed across a suspicious bag and placed inside the trace detection machine, can be accomplished with a robot working in collaboration with a human supervisor.

Baxter, developed by Rethink Robotics, enables humans to intuitively interact with robots in close proximity.

Because one of Baxter’s target markets is production floors, the robot is designed with work on a conveyor line in mind. Baxter is able to: (1) work safely alongside people, without the need for protective cages; (2) operate collaboratively through a unique, user-friendly UI; (3) be trained manually by line workers, with no programming required; and (4) respond adaptively to changes in its environment.

The automated testbed presented here is comprised of a Baxter research robot for luggage and object manipulation, and a down-looking overhead RGB-D sensor for inspection and detection. By looking at the TSA prohibited items list, one item in particular is relatively common and likely to be left in bags accidentally: the lighter. Lighters pose a risk to aircraft because they are pressurized, and if the fuel disperses as a mist in the cargo hold, due to failure of the pressure vessel, it could cause a serious fire. In addition, due to their generally small physical size, they can be difficult to detect reliably. The aim of this case study is to create a software framework to demonstrate robotics enabled bag inspection.

The general structure of the software architecture is described as follows. We use the point cloud library (PCL) to implement plane segmentation, allowing us to remove the tabletop and other extra surfaces from the image data. We then create a masked image focused on the detection area. The image data is then processed using OpenCV’s template matching algorithm which has been trained apriori on synthetically generated distorted images of a lighter. When a lighter is detected, its 3D position with respect to the sensor is calculated. This is translated into robot-centric coordinates through ROS’s TF tool. The path controller generates waypoints to the pickup of the lighter and this information is forwarded into the MoveIt tool which handles motion planning using OMPL. Finally, the generated trajectory is sent to Baxter through the API and Baxter picks up the lighter. The same process using MoveIt is then repeated to place the placard in the bag. Overall, the paper will demonstrate the effectiveness of the developed software architecture in a proof of concept system showing how Baxter or a similar robot could be used in a security inspection scenario.


    The DRC is a competition of robot systems and software teams vying to develop robots capable of assisting humans in responding to natural and man-made disasters. It was designed to be extremely difficult. Participating teams, representing some of the most advanced robotics research and development organizations in the world, are collaborating and innovating on a very short timeline to develop the hardware, software, sensors, and human-machine control interfaces that will enable their robots to complete a series of challenge tasks selected by DARPA for their relevance to disaster response. Three sequential DRC events place equal emphasis on hardware and software:

  • The Virtual Robotics Challenge occurred in June 2013 and tested software teams’ ability to effectively guide a simulated robot through three sample tasks in a virtual environment.
  • The DRC Trials occured December 20-21, 2013 at the Homestead-Miami Speedway, where teams guided their robots through eight individual, physical tasks that tested mobility, manipulation, dexterity, perception, and operator control mechanisms.
  • The DRC Finals occured June 5-6, 2015 at the Fairplex in Pomona, CA. Robots were required to attempt a circuit of consecutive physical tasks, with degraded communications between the robots and their operators. The winning team received a $2 million prize.

Technologies resulting from the DRC will transform the field of robotics and catapult forward development of robots featuring task-level autonomy that can operate in the hazardous, degraded conditions common in disaster zones. For more information on the challenge visit

WPI Team 2015

WPI Team 2013


Team WPI-CMU (Formally Team WRECS) is a collaborative effort involving aproximatly 30 team members from Worcester Polytechnic Institute and Carnegie Mellon University. The team members have a variety of expertise in robotics software, balancing and walking behaviors, robot perception, project management, and professional software engineering. Co-principal investigators are WPI professors Michael Gennert and Taşkın Padır, along with CMU professor Christopher Atkeson, while the team leader is Mathew DeDonato of WPI. Team WPI-CMU strives to foster a dedicated and well-managed team, composed of students, professors, and professional engineers, collaborating to discover and lead the state-of-the-art research enabling advanced human-level performance for the Atlas humanoid. We aim to publicly demonstrate the successful completion of tasks related to major disaster response with the intent of leading to relevant peer-reviewed publications, credibility for future DARPA solicitations, and the ultimate goal of winning the DARPA Robotics Challenge. For more information on the team visit



DRC Finals Score

The DRC Finals competition challenged participating robotics teams and their robots to complete a difficult course of eight tasks relevant to disaster response, among them driving alone, walking through rubble, tripping circuit breakers, turning valves and climbing stairs. A dozen teams from the United States and another eleven from Japan, Germany, Italy, Republic of Korea and Hong Kong competed in the outdoor competition.


DRC Trials Score

Sixteen teams from around the world came together at Florida’s Homestead Miami Speedway, December 20-21, 2013 to participate in DARPA’s Robotics Challenge Trials. The Trials provide an important baseline on the current state of robotics today and their potential for future use in disaster response. Team WRECS attempted all eight tasks, scoring points in five. The final results left us in 7th place, allowing us to move on to the finals and earning us another $1,500,000 in funding.


Published in:
2012 Ocean Science Meeting
Date of Conference:
February 20-24 2012
Conference Location:
Salt Lake City, Utah
Greg Gerbi, Emmanuel Boss, David Antoine, Andrew Barnard, Keith Brown, Mathew DeDonato, William Woodward
Measurements of Solar Radiation from an Autonomous Profiling Float: Opportunities and Results for Validation and Calibration Activities
Published in:
Ocean Optics XXI
Date of Conference:
October 8-12 2012
Conference Location:
Greg Gerbi, Emmanuel Boss, Robert Fleming, David Antoine, Keith Brown, Andrew Barnard, Mathew DeDonato, William Woodward
Use Of Autonomous Profiling Floats For Validation And Calibration Of Satellite Ocean Color Estimates
Published in:
IEEE International Conference on Systems, Man and Cybernetics
Date of Conference:
October 13-16 2013
Conference Location:
Velin Dimitrov, Mathew DeDonato, Adam Panzica, Samir Zutshi, Mitchell Wills, Taskın Padır
Hierarchical Navigation Architecture and Robotic Arm Controller for a Sample Return Rover
This work presents a hierarchical navigation architecture and cascade classifier for sample search and identification on a space exploration rover. A three tier navigation architecture and inverse Jacobian based robot arm controller are presented. The algorithms are implemented on AERO, the Autonomous Exploration Rover, participating in the NASA Sample Return Robot Centennial Challenge in 2013 and initial results are demonstrated.
Published in:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XIII, SPIE Defense + Security Conference
Date of Conference:
May 5-9 2014
Conference Location:
Baltimore, Maryland
Mathew DeDonato, Velin Dimitrov, Taskın Padır
Towards an Automated Checked Baggage Inspection System Augmented with Robots
We present a novel system for enhancing the efficiency and accuracy of checked baggage screening process at airports. The system requirements address the identification and retrieval of objects of interest that are prohibited in a checked luggage. The automated testbed is comprised of a Baxter research robot designed by Rethink Robotics for luggage and object manipulation, and a down-looking overhead RGB-D sensor for inspection and detection. We discuss an overview of current system implementations, areas of opportunity for improvements, robot system integration challenges, details of the proposed software architecture and experimental results from a case study for identifying various kinds of lighters in checked bags.
Published in:
Journal of Field Robotics
Date of Publication:
Feb 13 2015
Mathew DeDonato, Velin Dimitrov, Ruixiang Du, Ryan Giovacchini, Kevin Knoedler, Xianchao Long, Felipe Polido, Michael A. Gennert, Taşkın Padır, Siyuan Feng, Hirotaka Moriguchi, Eric Whitman, X. Xinjilefu and Christopher G. Atkeson
Human-in-the-loop Control of a Humanoid Robot for Disaster Response: A Report from the DARPA Robotics Challenge Trials
The DARPA Robotics Challenge (DRC) requires teams to integrate mobility, manipulation, and perception to accomplish several disaster-response tasks. We describe our hardware choices and software architecture, which enable human-in-the-loop control of a 28 degree-of-freedom Atlas humanoid robot over a limited bandwidth link. We discuss our methods, results, and lessons learned for the DRC Trials tasks. The effectiveness of our system architecture was demonstrated as the WPI-CMU DRC Team scored 11 out of a possible 32 points, ranked seventh (out of 16) at the DRC Trials, and was selected as a finalist for the DRC Finals.
Published in:
15th IEEE-RAS International Conference on Humanoid Robots
Date of Publication:
Nov 3 2015
Christopher. G. Atkeson, Benzun P. W. Babu, Nandan Banerjee, Dimitry Berenson, Chris P. Bove, Xiongyi Cui, Mathew DeDonato, Ruixiang Du, Siyuan Feng, Perry Franklin, Josh P. Graff, Peng He, Aaron Jaeger, Joohyung Kim, Kevin Knoedler, Lening Li, Chenggang Liu, Xianchao Long, Felipe Polido, Michael A. Gennert, Taskin Padir, Gregory G. Tighe, and X Xinjilefu
NO FALLS, NO RESETS: Reliable humanoid behavior in the DARPA Robotics Challenge
The DARPA We describe Team WPI-CMU’s approach to the DARPA Robotics Challenge (DRC), focusing on our strategy to avoid failures that required physical human intervention. We implemented safety features in our controller to detect potential catastrophic failures, stop the current behavior, and allow remote intervention by a human supervisor. Our safety methods and operator interface worked: we avoided catastrophe and remote operators could safely recover from difficult situations. We were the only team in the DRC Finals that attempted all tasks, scored points (14/16), did not require physical human intervention (a reset), and did not fall in the two missions during the two days of tests. We discuss lessons learned from the DRC.
Published in:
Journal of Field Robotics
Date of Publication:
Christopher. G. Atkeson, Benzun P. W. Babu, Nandan Banerjee, Dimitry Berenson, Chris P. Bove, Xiongyi Cui, Mathew DeDonato, Ruixiang Du, Siyuan Feng, Perry Franklin, Michael A. Gennert, Josh P. Graff, Peng He, Aaron Jaeger, Kevin Knoedler, Lening Li, Chenggang Liu, Xianchao Long, Taskin Padir, Felipe Polido, and X Xinjilefu
Team WPI-CMU: achieving reliable humanoid behavior in the DARPA Robotics Challenge
The DARPA The DARPA Robotics Challenge (DRC) required participating human-robot teams to integrate mobility, manipulation, perception and operator interfaces to complete a simulated disaster mission. We describe our approach to using the humanoid robot Atlas Unplugged developed by Boston Dynamics. We focus on our strategy to avoid failures that required physical human intervention: 1) extensive operator practice, 2) explicit “slow and steady” strategy, 3) explicit monitoring for robot errors, 4) adding additional superhuman sensing, and 5) enabling the operator to control and monitor the robot at varying degrees of abstraction. Our safety-first strategy worked: we avoided falling and remote operators could safely recover from difficult situations. We were the only team in the DRC Finals that attempted all tasks, scored points (14/16), did not require physical human intervention (a reset), and did not fall in the two missions during the two days of tests. We also had the most consistent pair of runs.


Publication Number:
US8954211 B2
Publication Type:
Application Number:
US 13/645,913
Publication Date:
Feb 10, 2015
Filing Date:
October 5, 2012
Mathew DeDonato
Original Assignee:
Teledyne Instruments, Inc.
Methods and Systems for Configuring Sensor Acquisition Based on Pressure Steps
Technologies are provided for underwater measurements. A system includes an underwater vessels including: a plurality of sensors disposed thereon for measuring underwater properties; and a programmable controller configured to selectively activate the plurality of sensors based at least in part on underwater pressure. A user may program at what pressure ranges certain sensors are activated to measure selected properties, and may also program the ascent/descent rate of the underwater vessel, which is correlated with the underwater pressure.