Madusudanan Sathia Narayanan PhD

Research Engineer The CORE Institute

Engineering Portfolio

Masters Thesis

Design of Masticatory Simulator using Parallel

Manipulator Architectures

Goal: Design and build a jaw

simulator to mimic the jaw

trajectories based on parallel

robotic architectures.

The thesis discusses the design of the simulator

based on engineering paradigm of Test-Evaluate-

Build. Hence, it first discusses about the

biomechanical analysis of the jaw using the model

of the joint kinematics and the motion capture

data. This is used to compute the jaw motion

envelope which the simulator should be capable of

tracking. The design of the masticatory simulator is

then decided based on the parallel robotic

architectures to give 6-DOF motion. A detailed

workspace singularity analysis of the simulator was

performed within the envelope of jaw motion and

then system was modeled kinematically and

dynamically using MATLAB/ SimMechanics and

DynaFlexPro.

CT and 3D Scanning- Dentition

Human and Canine Masticatory

Model

6-DOF Spatial Manipulators analysis

and dynamic modeling

Engineering Paradigm-

Build > Test > Evaluate

Prototyping and Testing

Parallel Mechanisms Kinematic

Simulation

Product Life Cycle Treatment by CAE Tools

Computer Aided Engineering

Computer-aided engineering (often referred to as CAE) is the use of information technology for supporting engineers in

tasks such as analysis, simulation, design, manufacture and planning CAE tools are being used. For instance, robustness

and performance analysis of components and assemblies. Among several of my projects, design and fabrication of a

tricycle for upper limb amputees is a notable one that fetched me a gold medal for the best design project. In this work

we look at application of CAE tools in each stages of product life cycle engineering in the context of fabricating a tricycle

for upper limb amputees

Concept Design/ Mechanism Synthesis Simulation

Material Optimization and

Stress Distribution (FEA) 3D CAD Model Fabricated Model

Analytical Models

Prototyping

Robotics and Mechatronics

Robotic and mechatronics systems are complicated control systems that combine

mechanical, electronic, and computer components such as motors, cameras, sensors,

actuators, software, and data acquisition hardware. Some of the projects I involved in the

Automation, Robotics and Mechatronics Laboratory (ARMLAB), are kinematic modeling

and control of wheeled mobile manipulator, creating seamless serial interface

communication with iRobot using remote control, developing a prototype and kinematic

level control of 6 DOF Stewart platform and simulation and building of masticatory

simulator.

To obtain the dynamic equations of a robotic system, automated symbolic computational

softwares are used like DynaFlexPro and SimMechanics. The results can then be compared

for the benchmark problems by manual derivations and extended to more complicated

robotic systems.

Cooperative Manipulation

and HIL Testing

Non-holonomic Control of Wheeled Mobile

Manipulators

Hardware Integration and Real Time Control

Implementation of Reconfigurable Systems

HIL Testing of Mechatronic Systems with Guidance Control

Robotic Testing of Surgical

Joint Implants

Surgical Joint Implants

Assessing human joint functions and its inter-relation with degenerative changes requires an

understanding of the normal state of structural loading in the joint. Very few studies have attempted to

reproduce joint specific in vivo motions in vitro. Even fewer have attempted to reproduce the realistic

muscle loading and lines of action. In this work, we designed and fabricated novel servo-controlled

robotic testbeds that addresses these aspects and enables us to precisely control muscle loading

patterns for various joint motions. Such a framework further makes it possible to test various surgical joint

implants and medical devices under realistic and cyclical conditions, and take quantitatively driven

design decisions for overall performance improvement.

Modular Design Improvement

Modular Design Improvement Shoulder Joint

Testing

In-vivo Joint Testing

Robotic Lower Extremity Testing

Automotive Design

Road Wideners

Despite the rapid penetration of CAE tools, many

companies still rely on decades old engineering sketches

which as in most cases turn out to be economically

favorable in the short run. However, the integration of CAE

framework is not simply computerizing all the design

processes but by doing that it provides a viable platform to

quickly realize the path of quantitative design and of

continuous improvement thereby providing a competitive

edge over the competitors in the long run. Midland

Machinery is one such company who realized the potential

of CAE tools and immediately sought for professional

engineering services to revamp their product development

process and generate part and assembly drawings through

CAD software for their new upgraded product line (SP-12

road widener vehicle). In addition to well-known benefits

such as optimization of material-cost, product layout and

generating part drawings, notable accomplishments

include performing computational (finite elements) stress

analysis of their critical components (vehicle chassis,

steering module, blade assembly and blade extender units).

Dynamics and Controls

Formulating the dynamic model of a mechanical system involves tedious

differential mathematics. The complexity is increased manifold by presence

of nonlinearities in virtually every model of a real mechanical system. In order

to devise control algorithms for such systems, a separate branch of controls-

Nonlinear control techniques must be implemented. This is used behavior of

a nonlinear system cannot be described as a linear function of the state of

that system or the input variables to that system. For linear systems, there are

many well-established control techniques, for example root-locus, Bode plot,

Nyquist criterion, state-feedback, pole-placement etc. My projects covered

either of these aspects in the context of dual finger manipulation and driving

simulator respectively. The feedback linearization technique is used to deal

with the nonlinearities in the Lagrangian equations of motion for the system

and suitable decoupling laws are derived to simultaneously control trajectory

and force profiles.

For linear transient systems, the stability characteristics are analyzed to design

a lead compensator controller to achieve better transient characterisitics of

the system. The linear compensated system Is then simulated using virtual

haptic environment with Sensable Phantom Omni Device.

Nonlinear Control of Dual Finger Manipulators Haptics Based Human-in-the-Loop Driving Simulator and

Controller Design

Model-based Control

Robotic Surgical Interventions

Evaluating performance of surgeons and developing high fidelity assistive systems and methods to aid in performing these procedures efficiently are

challenging tasks. Such robotic assistants are feasible today and primarily rely on model-based controllers derived from real-time measurements using

sensorized tools and preoperative clinical datasets (such as CT scans). Specifically, in-parallel robotic systems will be validated for surgical training applications

to seek skill improvement and demonstrated as suitable candidate for future automated robotic-surgical applications for precise procedures.

Biomedical and Healthcare

Systems Dissertation

Surgical Simulators and Skill Assessment

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Expert, intermediate,Novice

Bar 3D plot for mean of all features

feature number

mean va

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Needle Insertion Simulator Framework Minimally Invasive Surgical Simulator Framework

Virtual and Physical Simulator

Robotic and Manual Insertions

Virtual and Physical

Simulator

Robotic Teleoperation

Forward Inflow Outflow

Forward Inflow Outflow

Computational Modeling and Software Development

Virtual Musculoskeletal

Anatomical Case Studies

Finite Element Analysis code using COMSOL and

MATLAB

CAD Graphics Software

Nano manufacturing using Optical Tweezers

Contact Details:

Madusudanan Sathia Narayanan

Local Address 2250 NW Thorncroft Dr Apt 324

Hillsboro OR 97124

Email: madu.s.narayanan@gmail.com Cell: 716 435 6680

Web: www.madu-sathia.com