The following details various research projects that are currently active.

Human-in-the-loop Augmented Automatic Control and Vehicle Design

Optimal Bicycle Design for Handling

Current researchers: Anastasia Kubicki, Anthony Toribio
Collaborators: Mont Hubbard, Ronald Hess (UC Davis)
Past researchers: Roy Gilboa
Image of a theorectical optimal bicycle.

We have developed an optimization algorithm that can discover bicycle designs which maximize the lateral handling qualities of the vehicle [1]. The algorithm produces less-than-intuitive but physically feasible bicycle designs. We are currently working to make the algorithm more robust and expanding the parameter search space. We are also constructing some of the discovered designs for experimental validation and testing. The first design, based on an optimal design for 4 m/s is shown below:

Image of a realizable optimal bicycle.
[1]Moore, Jason, Mont Hubbard, and Ronald A. Hess. "An Optimal Handling Bicycle." In Proceedings of the 2016 Bicycle and Motorcycle Dynamics Conference. Figshare, 2016.

Experimental Validation of Bicycle Handling Prediction

Current researchers: Trevor Metz
Collaborators: Mont Hubbard, Ronald Hess
Past researchers: Scott Kresie
Image showing handling quality metrics for a variety of bicycles.

We have proposed a theoretical lateral handling quality metric for any given bicycle design based on a corpus of experimental data in aircraft handling research [2]. This project aims to validate this metric directly from experimental evidence in bicycling maneuvers and tasks. We have developed a variable stability instrumented bicycle and demonstrated preliminarily that that there may be correlations between our theoretical metric and the rider's subjective opinion of the bicycle's handling [3]. Ongoing work includes, improvements to the experimental apparatus and protocol for a larger scale validation with arbitrary experimental subjects [4].

[2]Hess, Ronald, Jason K. Moore, and Mont Hubbard. "Modeling the Manually Controlled Bicycle." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 42, no. 3 (May 2012): 545–57.
[3]Kresie, Scott W., Jason K. Moore, Mont Hubbard, and Ronald A. Hess. "Experimental Validation of Bicycle Handling Prediction," September 13, 2017.
[4]Metz, Trevor. "Design of a PID Controller for Controlling The Speed of an Instrumented Ebike", Laboratorium of Marvelous Mechanical Motum Blog (December 15, 2018)

Assistive Device Design for the Physically Impaired

Control Identification of Human Standing

Current researchers:
Collaborators: Ton van den Bogert (Cleveland State University)
Past researchers: Dorian Crutcher, Jonathan Cubanski, Todd Sweeney, Greg McDonald, Jiahao Wei, Erich Baur, Kendall Lui, Stanley Tsang, Chenxiong Yi, Rouxi Peng

Humans unconsciously utilize a control strategy while standing. Visual, vestibular, and proprioceptive sensing inform the brain's control strategy which reacts to internally and environmentally produced perturbations. This is something humans are very good at but robots are bad at, thus if we can understand how humans accomplish this we can potentially design robots with biomimetic controllers. In laboratory settings we can accurately measure body segment kinematics, muscle activation levels, and ground force reactions during standing. Given all or subsets of this data collected during externally perturbed standing, we are interested in developing optimal control theories and methods of identifying the specific control strategy in use. We have developed parameter identification methods using direct collocation to identify the controllers used in simulated standing [5]. The general optimal control and parameter estimation methods used have been formalized in the software, Opty [6]. We are currently developing a small desktop "double pendulum on a cart" robot to verify and improve the control identification methods. The robot will allow us to measure the motion during perturbed balancing which is a result of known programmed control strategies.

[5]Moore, Jason K., and Antonie J. van den Bogert. "Quiet Standing Control Parameter Identification with Direct Collocation." In XV International Symposium on Computer Simulation in Biomechanics. Edinburgh, UK, 2015.
[6]Jason K. Moore, and Antonie van den Bogert. "Opty: Software for Trajectory Optimization and Parameter Identification Using Direct Collocation." Journal of Open Source Software 3, no. 21 (2018): 300.

Design of a Quadriplegic Friendly Tricycle

Current researchers:
Collaborators: Greg Tanner (Disability Reports), Tommy Ausherman (Outrider USA)
Past researchers: Aaron Shaw, Jake Parkhurst, Andy Wu, Felicia Fashanu, Haowei Li, Cynthia Devaughn, Vivian Ting, Thomas Poozhikala
brochure image of the tricycle

Students developed a adaptive input device to enable persons with ALS or quadriplegia to control an electric tricycle.

Enhancing Athlete Performance and Safety in Sports

Smartphone-based Rowing Metric Estimation

Current researchers:
Collaborators: Paul Crawford (Hegemony Technologies), Mont Hubbard (UC Davis), Xinfan Lin (UC Davis)
Past researchers: Bryn Cloud, Ada Liu, Britt Tarien, Thomas Shedd, Li Wang, Andrew Shoats

Real-time feedback of stroke-by-stroke rowing performance metrics can enable data driven training and coaching. Instrumenting rowers during training and competition with laboratory quality sensing is very difficult, but the ubiquity of smartphones provides an avenue to collect fewer and less accurate kinematic and kinetic measurements. This project aims to improve performance critical biomechanic rowing metrics through dynamics informed estimation algorithms. We have developed rower adaptive filtering methods to predict global boat position, speed, stroke rate, and distance per stroke at high accuracy and with experimental protocols for validating the estimations [7].

[7]B. Cloud et al., "Adaptive smartphone-based sensor fusion for estimating competitive rowing kinematic metrics," 23-Dec-2018.

Ski Jumps Designed for a Specific Equivalent Fall Height

Current researchers: Bryn Cloud
Collaborators: Britt Tarien, Mont Hubbard (UC Davis), Jim McNeil (Colorado School of Mines)
Screenshot of the ski jump design application.

Little engineering or science goes into the design and construction of ski and snowboard jumps in terrain parks at publicly accessible ski resorts. A relatively large number of injuries and even deaths occur during skiing and snowboarding at these resorts. It is possible to design the landing surfaces of jumps such that the normal impact velocity on landing is capped at a safer value regardless of the jumper's takeoff speed and jump launch speed. These jump designs can still provide large maximum heights and flight durations. We have designed a web application that laymen can use to design ski jumps with a specified equivalent fall height.

Sustainable Transportation

Inexpensive Open Source and Open Hardware Bicycle Data Logger

Current researchers:
Past researchers: Edward Jacobs
Collaborators: Marco Dozza (Chalmers University), Christian-Nils Åkerberg Boda (Chalmers University)

Analysis of comprehensive dynamical data during bicycling trips and activities has the potential to teach us much about travel behavior and safety of bicyclists. We would like to develop a open collaborative project with the aim of creating a modular, continually inexpensive, open source, and open hardware bicycle data logger. This idea was pitched by Marco Dozza at ICSC 2017 [8] and we are working with his team to bring this to fruition.

[8]Dozza, Marco; Rasch, A.; Boda, C. N. (2017): An Open-Source Data Logger for Field Cycling Collection: Design and Evaluation.

Human Powered Appropriate Technology

Efficiency of Human Powered Irrigation Pumps

Current researchers:
Collaborators: Andrew Hall (Buffalo Bikes)
Past researchers: Aaron Shaw, Rayming Liang, Abraham McKay

We have developed a inexpensive centrifugal pump that attaches to a simple power takeoff on a Buffalo Bike [9]. Our hypothesis is that a less efficient centrifugal pump paired with power generation from cycling will be overall more efficient than a more efficient positive displacement pump paired with stepping power generation. We have recently shown this to be true by accurately measuring the input biomechanical power and output hydraulic power from both systems to produce efficiency curves as a function of hydraulic load [10].

[9]Mckay, Abraham B., "The Water Buffalo: Design of a Portable Bicycle Powered Irrigation Pump for Small-Scale African Farmers", MSc Thesis, University of California, Davis, 2018.
[10]Shaw, Aaron and Liang, Rayming. "Finding the Efficiency of the Xylem and Money Maker Treadle Pumps", Laboratorium of Marvelous Mechanical Motum Blog (December 27, 2018)

Teaching and Learning Engineering Through Mobility Applications

Learning Mechanical Vibrations Through Computational Thinking

Current researchers:
Past researchers: Kenneth Lyons

"Computational thinking" is an alternative learning process for formulating and solving engineering problems. A unique set of abstractions are available to the learner in addition to those from mathematical and written language. We have developed an interactive textbook and problem sets using the Jupyter system of tools for 40 hours of in-class teaching and learning. These teaching materials are backed by a custom software library for mechanical vibrations designed to facilitate solving problems with computational thinking.

Interactive Jupyter-Enabled LibreTexts Pages

Current researchers: Celine Liang
Collaborators: Delmar Larsen (UC Davis), Richard Feltstykket (UC Davis), Tom Neubarth (UC Davis)
Past researchers: Xiaochen Zang, Xin Luigi Chen, Kevin Krausse, Henry Agnew

We are interested in providing an interactive computing environments in online textbooks at a massive scale. LibreTexts is one of the largest and most visited online compendium of textbooks used in collegiate academics. The website currently serves mostly static and non-interactive content. We are working to enable Jupyter-backed interactive computation cells that authors can use to incorporate Python, R, Octave, and Sage generated media for pages. This will enable arbitrary visualizations and allow students to learn through computational oriented exercises.

Development of a Beam Bending Package for SymPy

Current researchers: Ishan Joshi (Netaji Subhas Institute of Technology, SymPy GSoC)
Collaborators: SymPy Developers
Past researchers: Jashanpreet Singh, Sampad Saha

Mechanical and civil engineers utilize two- and three-dimensional theories of stress and strain to determine if structural beams will fail. Simple mathematical models can be used to make accurate predictions of failure due to shear, bending, and torsion stresses and due to deflection. Solving beam related problems typically involves integrating discontinuous functions and solving for boundary conditions. The integral calculus and algebra details often hide the trees for the woods. This project is centered around developing a package for SymPy that can be used to model and solve analytical beam problems, without getting bogged down in the mathematical details.