Master of Science (M.S.), University of Dayton, 2021, Mechanical Engineering

Being able to determine a person's center of mass (COM) location is very important and useful to many studies, but not easily calculated. COM is used in a variety of studies, especially those dealing with balance, as COM must be over the center of pressure (COP) for something to maintain balance in a static position. An open-source software called OpenSim has its own COM estimation built into its Residual Reduction Algorithm (RRA) and is widely used in the field of biomechanics. This study seeks to compare the accuracy of this estimation to a recently developed COM estimation method called the Statically Equivalent Serial Chain (SESC) estimation. This study uses data collected via motion capture and force plates to further validate the SESC method as well as compare its accuracy to that of the currently implemented RRA through motion capture and data processing in OpenSim and MATLAB. Motion capture data provided an accurate representation of subject kinematics used in both COM estimations, and force plate COP as the metric for comparison in the horizontal directions. For data collection, 1 PVC humanoid and 16 subjects between the ages of 18 and 50, stood in 40 static poses. The poses were initially processed through the motion capture software, Vicon Nexus, and then inverse kinematics, dynamics, and RRA in OpenSim. Finally, the SESC COM estimation was determined using this processed data through a custom MATLAB script, and the magnitude of the error in the horizontal plane of all subjects' poses was analyzed. The SESC estimation proved to be significantly better than the OpenSim estimation using RRA through analysis of variance (ANOVA) testing, with an average error of 7.82 mm for SESC and 10.69 mm for RRA (p<0.0001, P=0.99). Additionally, the SESC error maintained its accuracy within this new experimental study, being below the maximum error of previous COM estimation studies. This study differs from other studies because of its more developed breakdown of the h (open full item for complete abstract)

Committee: Allison Kinney (Advisor); Andrew Murray (Committee Member); Megan Reissman (Committee Member) Subjects: Biomechanics; Mechanical Engineering

Doctor of Philosophy (Ph.D.), University of Dayton, 2015, Mechanical Engineering

This dissertation presents a center of mass (CoM) estimation technique that uses the statically equivalent serial chain (SESC). A SESC is a representation of any multilink branched chain whose end-effector locates the CoM. Identifying the center of mass location provides a significant aid in controlling the balance of humanoid robots. Additionally, in humans this location is an essential parameter in postural control and is critical in assessing rehabilitation. Anthropometric tables have been complied for this identification but their accuracy is readily questioned. The method starts with an experimental phase involving a force plate and a motion capture system (MoCap) to construct a model to predict the CoM location. Subsequent motion of the subject updates the CoM model based on MoCap information without need of a force plate, overcoming disadvantages of some other CoM estimation methods. The node-based SESC model is developed to best integrate with Kinect and the likely MoCap systems that will be developed in the near future. The results show that the SESC methodology allows rapid and accurate real time estimation of the CoM. The transfer-ability of the SESC parameters among subjects with similar body structure using the donor model is also presented. The donor model allow subjects to perform fewer postures in the experimental phase to generate a SESC. The donor model facilitates the identification of a SESC for subjects with limited mobility. This work includes the CoM estimation for human subjects using low-end and high-end MoCap and force plate sensors. The high-end and low-end MoCap and force plate sensors are used for cross validation and to show that the method is applicable to both systems. Additionally, the presence of a static body in the workspace (a walker or chair, for example) to create stability in test subjects is presented. The introduction of the static body aids in balance and stability and adds more postures to agile subjects. Furthermor (open full item for complete abstract)

Committee: Andrew Murray Professor (Committee Chair); David Myszka Associate Professor (Committee Member); Raul Ordonez Professor (Committee Member); David Perkins Lecturer (Committee Member) Subjects: Biomechanics; Mechanical Engineering; Robotics

Master of Science (M.S.), University of Dayton, 2014, Electrical Engineering

This thesis describes the development of a real-time, open source, easily programmed and controlled platform to replace the existing Manoi AT01 humanoid robot. Processing language was used as a control and implements the Graphical User Interface (GUI) and an Arduino Mega development board and an SD21 servo-driver were used to implement the controller and data acquisition. The designed platform is also used to measure and calculate the Center of Pressure (CoP) of the robot. For this purpose, Force Sensitive Resistor (FSR) sensors are used to measure the force exerted by the weight of the robot. Four sensors were used and are positioned on the corners of a specially designed plastic feet attached to each leg. The CoP is calculated by the Arduino and displayed in real time on the GUI. In order to determine the Center of Mass (CoM), the Statically Equivalent Serial Chain (SESC) model is adopted. This model is implemented using MATLAB. The implemented GUI provides a function that allows the user to create a file for storing the position of each servo and the CoP of different scenarios. These data files are used as the input to the SESC model program in order to estimate the CoM of the robot.

Committee: Raul Ordonez (Committee Chair); Daniels Malcolm (Committee Member); Barrera Ralph (Committee Member) Subjects: Electrical Engineering

Master of Science (M.S.), University of Dayton, 2013, Mechanical Engineering

Any system composed of rigid bodies connected by revolute, spherical, and/or universal joints defines a Statically Equivalent Serial Chain (SESC). The SESC is a virtual serial chain that terminates at the center of mass (CoM) of the original system. The SESC is defined by the individual link masses, the CoM location of each mass, the distance between the joints, and the relative joint axis orientations. The joint angles of the SESC change corresponding to the movement of the original system, thereby keeping its terminus pointing at the CoM location of the original system for any configuration. A SESC may be generated experimentally without any knowledge of the individual link masses, the CoM location of each mass, and the distance between the joints. The data that is needed includes the relative orientations between joint axes, the current joint values, and the CoM of the entire articulated system. In most cases, the SESC can be derived with only partial CoM information collected for each configuration. An example of this is collecting the x and y values of the CoM in a horizontal plane while not knowing its height or z value. The resulting SESC is able to generate the location of the CoM for an arbitrary configuration given the joint angles. Necessary conditions are generated on the minimum number of data points needed to generate a SESC. The minimum number needed depends on the number of links of the original system, the dimension of the CoM data collected for each configuration, and a measure of the degree of redundancy in the columns of the matrix associated with the initial SESC modeling. This thesis presents four developments toward recognizing the SESC as a practical modeling technique. First, modifications to a matrix necessary in computing the SESC model are proposed. The modifications are required due to redundant columns that arise in the matrix as part of the modelling process. Second, a SESC is developed via experimentation for a spatial articulat (open full item for complete abstract)

Committee: Andrew Murray Ph.D. (Advisor); David Myszka Ph.D. (Committee Member); Raul Ordonez Ph.D. (Committee Member) Subjects: Mechanical Engineering