Monroe Kennedy III
Assistant Professor of Mechanical Engineering
Bio
Monroe Kennedy III is an Assistant Professor of Mechanical Engineering, with a courtesy appointment in Computer Science. He is the recipient of the NSF Career Award. He received his Ph.D. in Mechanical Engineering and Applied Mechanics, and a Masters in Robotics from the University of Pennsylvania where he was a recipient of both the NSF and GEM graduate research fellowships. His area of expertise is in collaborative robotics, specifically the development of theoretical and experimental approaches to enhance robotic autonomy and robotic effectiveness in decentralized tasks toward human-robot collaboration. He applies expertise in machine learning, computer vision, collaborative robot teammate intent estimation, dynamical systems analysis, control theory (classical, non-linear, and robust control), state estimation and prediction, and motion planning.
He is the director of the Assistive Robotics and Manipulation Lab (ARMLab) whose broad research objective is to develop technology that improves everyday life by anticipating and acting on the needs of human counterparts. ARMLab specializes in developing intelligent robotic systems that can perceive and model environments, humans, and tasks and leverage these models to predict system processes and understand their assistive role. The research can be divided into the following sub-categories: robotic assistants, connected devices, and intelligent wearables. ARMLab research requires the use of a combination of tools in dynamical systems analysis, control theory (classical, non-linear, and robust control), state estimation and prediction, motion planning, vision for robotic autonomy, teammate intent estimation, and machine learning. ARMLab focuses heavily on both the analytical and experimental components of collaborative robotics. Research applications include autonomous assistive technology, robotic assistants (mobile manipulators and humanoids) with the goal of deployment for service tasks that may be highly dynamic and require dexterity, situational awareness, and human-robot collaboration.
Academic Appointments
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Assistant Professor, Mechanical Engineering
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Member, Bio-X
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Faculty Affiliate, Institute for Human-Centered Artificial Intelligence (HAI)
Honors & Awards
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Faculty Early Career Award, National Science Foundation (February 24, 2022)
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Graduate Research Fellowship, National Science Foundation (2013-2018)
Boards, Advisory Committees, Professional Organizations
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Member, American Society of Mechanical Engineers (2015 - Present)
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Member, Institute of Electrical and Electronics Engineers (2016 - Present)
Professional Education
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PhD, University of Pennsylvania, Mechanical Engineering and Applied Mechanics (2019)
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MS, University of Pennsylvania, Robotics (2016)
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BS, University of Maryland, Baltimore County, Mechanical Engineering (2012)
Community and International Work
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National Director for Black in Robotics
Topic
Increasing engagement of underrepresented minorities in robotics
Partnering Organization(s)
Black in Robotics
Populations Served
High school, college and academic/industry professionals
Location
International
Ongoing Project
Yes
Opportunities for Student Involvement
No
Current Research and Scholarly Interests
My research is to develop technology that improves everyday life by anticipating and acting on the needs of human counterparts. The research can be divided into the following sub-categories: robotic assistants, connected devices and intelligent wearables. I use a combination of tools in dynamical systems analysis, control theory (classical, non-linear and robust control), state estimation and prediction, motion planning, vision for robotic autonomy and machine learning. My Assistive Robotics and Manipulation lab (arm.stanford.edu) focuses heavily on both the analytical and experimental components of assistive technology design. While our application area domain is autonomous assistive technology, our primary focus is robotic assistants (mobile manipulators and humanoids) with the goal of deployment for service tasks that may be highly dynamic and require dexterity, situational awareness, and human-robot collaboration.
2024-25 Courses
- Collaborative Robotics
CS 339R, ME 326 (Win) - Dynamics
ENGR 15 (Aut) - Robotic Dexterity: Principles and Practice
ME 314 (Spr) -
Independent Studies (18)
- Advanced Reading and Research
CS 499 (Aut, Win, Spr, Sum) - Advanced Reading and Research
CS 499P (Aut, Win, Spr, Sum) - Curricular Practical Training
CS 390A (Aut, Win, Spr, Sum) - Curricular Practical Training
CS 390B (Aut, Win, Sum) - Curricular Practical Training
CS 390C (Aut, Win, Sum) - Engineering Problems
ME 391 (Aut, Win, Spr, Sum) - Engineering Problems and Experimental Investigation
ME 191 (Aut, Win, Spr, Sum) - Experimental Investigation of Engineering Problems
ME 392 (Aut, Win, Spr, Sum) - Honors Research
ME 191H (Aut, Win, Spr, Sum) - Master's Directed Research
ME 393 (Aut, Win, Spr, Sum) - Master's Directed Research: Writing the Report
ME 393W (Aut, Win, Spr, Sum) - Part-time Curricular Practical Training
CS 390D (Aut, Win, Sum) - Ph.D. Research Rotation
ME 398 (Aut, Win, Spr, Sum) - Ph.D. Teaching Experience
ME 491 (Aut, Win, Spr) - Practical Training
ME 199A (Win, Spr) - Practical Training
ME 299A (Aut, Win, Spr, Sum) - Practical Training
ME 299B (Aut, Win, Spr, Sum) - Problems in Aero/Astro
AA 290 (Aut, Win, Spr)
- Advanced Reading and Research
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Prior Year Courses
2023-24 Courses
- Advanced Dynamics, Modeling and Analysis
ME 334 (Spr) - Collaborative Robotics
CS 339R, ME 326 (Win) - Dynamics
ENGR 15 (Aut)
2022-23 Courses
- Advanced Dynamics
ME 334 (Spr) - Collaborative Robotics
CS 339R, ME 326 (Win)
2021-22 Courses
- Advanced Dynamics, Controls and System Identification
ME 334 (Spr) - Collaborative Robotics
ME 326 (Win) - Dynamics
ENGR 15 (Aut)
- Advanced Dynamics, Modeling and Analysis
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Dylan Asmar, Julia Di, Marion Lepert, Jasmin Palmer, Adrian Piedra, Gadi Sznaier Camps, Trey Weber, Javier Yu -
Orals Chair
Joshua Ott -
Doctoral Dissertation Advisor (AC)
Won Kyung Do, Shivani Guptasarma, Aliyah Smith -
Master's Program Advisor
Manuel Abitia Leon, Zahra Albasri, Omoruyi Atekha, Liam Campbell, Alexander Chen, Catherine Chen, Wilson Chen, Winnie Chen, Aditya Dutt, Yunxin Fan, Naixiang Gao, Romeo Garcia, Xiaolong Jia, Joonwon Kang, Brian LaBlanc, Joshua Lee, Mark Leone, Yu Wei Lin, Rosalie Massein, Chetan Reddy Narayanaswamy, Seth Nguyen, Wei-Lin Pai, Paul Portmann, Nattakit Tankongchamruskul, Cyrus Xiang, Austin Yang, Qianhe Ye, Yazhou Zhang -
Doctoral Dissertation Co-Advisor (AC)
William Chong, Chinmay Devmalya, Ken Wang, Josiah Wong -
Doctoral (Program)
Nicholas Broadbent, Max Burns, Shivani Guptasarma, William Heap, Shalika Neelaveni, Jinho So, Matt Strong, Aiden Swann
All Publications
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Inter-finger Small Object Manipulation With DenseTact Optical Tactile Sensor
IEEE ROBOTICS AND AUTOMATION LETTERS
2024; 9 (1): 515-522
View details for DOI 10.1109/LRA.2023.3333735
View details for Web of Science ID 001123441400014
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The role of collaborative robotics in assistive and rehabilitation applications.
Science robotics
2023; 8 (83): eadk6743
Abstract
Collaborative robotics principles and advancements may transform the field of assistive and rehabilitation robotics.
View details for DOI 10.1126/scirobotics.adk6743
View details for PubMedID 37878691
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Trajectory and Sway Prediction Towards Fall Prevention.
IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation
2023; 2023: 10483-10489
Abstract
Falls are the leading cause of fatal and non-fatal injuries, particularly for older persons. Imbalance can result from the body's internal causes (illness), or external causes (active or passive perturbation). Active perturbation results from applying an external force to a person, while passive perturbation results from human motion interacting with a static obstacle. This work proposes a metric that allows for the monitoring of the persons torso and its correlation to active and passive perturbations. We show that large changes in the torso sway can be strongly correlated to active perturbations. We also show that we can reasonably predict the future path and expected change in torso sway by conditioning the expected path and torso sway on the past trajectory, torso motion, and the surrounding scene. This could have direct future applications to fall prevention. Results demonstrate that the torso sway is strongly correlated with perturbations. And our model is able to make use of the visual cues presented in the panorama and condition the prediction accordingly.
View details for DOI 10.1109/icra48891.2023.10161361
View details for PubMedID 38009123
View details for PubMedCentralID PMC10671274
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Diffusion Co-Policy for Synergistic Human-Robot Collaborative Tasks
IEEE Robotics and Automation Letters
2023: 1-8
View details for DOI 10.1109/LRA.2023.3330663
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Trajectory and Sway Prediction Towards Fall Prevention
2023: 10483-10489
View details for DOI 10.1109/ICRA48891.2023.10161361
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It Takes Two: Learning to Plan for Human-Robot Cooperative Carrying
2023: 7526-7532
View details for DOI 10.1109/ICRA48891.2023.10161386
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DenseTact 2.0: Optical Tactile Sensor for Shape and Force Reconstruction
2023: 12549-12555
View details for DOI 10.1109/ICRA48891.2023.10161150
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DenseTact: Optical Tactile Sensor for Dense Shape Reconstruction
2022: 6188-6194
View details for DOI 10.1109/ICRA46639.2022.9811966
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Replay Overshooting: Learning Stochastic Latent Dynamics with the Extended Kalman Filter
IEEE International Conference on Robotics and Automation
2021: 852-858
View details for DOI 10.1109/ICRA48506.2021.9560811
- Considerations for the Control Design of Augmentative Robots IEEE IROS Workshop on Building and Evaluating Ethical Robotic Systems. 2021
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Robots are not immune to bias and injustice.
Science robotics
2020; 5 (48)
Abstract
Human-human social constructs drive human-robot interactions; robotics is thus intertwined with issues surrounding inequity and racial injustices.
View details for DOI 10.1126/scirobotics.abf1364
View details for PubMedID 33208524
- Recent Development in Human Motion and Gait Prediction RSS 2020 Workshop RobRetro. 2020
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Autonomous Precision Pouring From Unknown Containers
IEEE ROBOTICS AND AUTOMATION LETTERS
2019; 4 (3): 2317–24
View details for DOI 10.1109/LRA.2019.2902075
View details for Web of Science ID 000462380600010
- Modeling And Control For Robotic Assistants: Single And Multi-Robot Manipulation Publicly Accessible Penn Dissertations. 2019 (3299):
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Optimal Paths for Polygonal Robots in SE(2)
ASME. 2018
View details for DOI 10.1115/1.4038980
View details for Web of Science ID 000426985200006
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Object Picking Through In-Hand Manipulation Using Passive End-Effectors With Zero Mobility
IEEE ROBOTICS AND AUTOMATION LETTERS
2018; 3 (2): 1096–1103
View details for DOI 10.1109/LRA.2018.2795652
View details for Web of Science ID 000424646100033
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Precise dispensing of liquids using visual feedback
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2017
View details for DOI 10.1109/IROS.2017.8202301
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Precise Dispensing of Liquids Using Visual Feedback
IEEE. 2017: 1260–66
View details for Web of Science ID 000426978201091
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A Triangle Histogram for Object Classification by Tactile Sensing
IEEE. 2016: 4931–38
View details for Web of Science ID 000391921704140
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DECENTRALIZED ALGORITHM FOR FORCE DISTRIBUTION WITH APPLICATIONS TO COOPERATIVE TRANSPORT
AMER SOC MECHANICAL ENGINEERS. 2016
View details for Web of Science ID 000380413600013
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Decentralized Algorithm for Force Distribution With Applications to Cooperative Transport
International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
2015
View details for DOI 10.1115/DETC2015-47752
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Automated biomanipulation of single cells using magnetic microrobots
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
2013; 32 (3): 346–59
View details for DOI 10.1177/0278364912472381
View details for Web of Science ID 000317693400005