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Morris Wachira

Researcher | Bioengineering, Nanotechnology & Robotics

Researcher with interests in bioengineering, nanotechnology, robotics, and modeling of engineering systems.

About Morris Wachira

Morris Wachira is a researcher with interests spanning bioengineering, nanotechnology, robotics, and modeling of engineering systems. His multidisciplinary background bridges biological systems, nanoscale phenomena, robotic control, and computational methods for analyzing complex engineering problems.

Focus

⚙️ Bioengineering
Nanotechnology
🤖 Robotics
⚙️ Modeling of Engineering Systems

📚 Education Contributions

Robotics

Lesson 2: Forward and Inverse Kinematics

Compute end-effector positions from joint angles and solve inverse kinematics for robotic welding, assembly, and precision positioning

Published: March 10, 2026

roboticsforward-kinematicsinverse-kinematicsDH-parametersend-effectorrobotic-weldingnumerical-IK

Lesson 3: Orientation and Quaternions

Represent 3D orientations using quaternions for smooth robotic motion, avoiding gimbal lock with SLERP interpolation and rotation composition

Published: March 10, 2026

roboticsquaternionseuler-anglesgimbal-lockSLERProtationorientation-controldrone-gimbal

Lesson 1: Robot Arm Geometry and Configuration

Analyze robot arm link design, joint types, workspace boundaries, and common configurations including SCARA, articulated, and delta robots

Published: March 10, 2026

roboticsrobot-armworkspace-analysisjoint-typesSCARAarticulated-robotdelta-robotlink-design

Lesson 6: Robot Simulation and Practical Applications

Build Python robot simulations with real-time visualization and apply robotics across manufacturing, medical, logistics, and agricultural domains

Published: March 10, 2026

roboticssimulationmatplotlib-animationmanufacturingsurgical-roboticsagricultural-roboticspick-and-placevisualization

Lesson 5: Trajectory Planning and Motion Control

Plan smooth robot trajectories using polynomial interpolation, splines, and velocity profiles for pick-and-place and path following tasks

Published: March 10, 2026

roboticstrajectory-planningmotion-controlpick-and-placepolynomial-interpolationsplinevelocity-profilepath-planning

Lesson 4: Velocity Kinematics and the Jacobian

Derive and apply the Jacobian matrix for velocity mapping, singularity detection, and manipulability analysis in collaborative robots

Published: March 10, 2026

roboticsjacobian-matrixvelocity-kinematicssingularitymanipulabilitycollaborative-robotpseudoinverseforce-mapping
Applied Mathematics

Feedback and Control Systems

Measure the output, compare to the desired value, adjust the input. That is feedback. This lesson covers PID control from intuition to implementation.

Published: March 9, 2026

PIDcontrol-systemsfeedbackZiegler-Nicholsstabilityapplied-mathengineering

Numerical Methods: Math in Code

Computers do arithmetic, not calculus. Learn root finding, numerical integration, interpolation, curve fitting, and the Runge-Kutta ODE solver.

Published: March 8, 2026

numerical-methodsroot-findingintegrationinterpolationcurve-fittingRK4applied-math

Fourier Analysis and the Frequency Domain

Any signal can be decomposed into sine waves. This lesson teaches you to see signals in the frequency domain, understand the FFT, and avoid aliasing.

Published: March 7, 2026

fourierFFTfrequency-domainsamplingNyquistaliasingapplied-mathsignal-processing

Differential Equations and Real Systems

A differential equation says the rate of change depends on the current value. RC circuits, spring-mass systems, and cooling all follow this pattern.

Published: March 6, 2026

differential-equationsRC-circuitspring-masseuler-methodapplied-mathengineering

Probability, Statistics, and Noise

Every sensor reading has noise. Learn to quantify uncertainty, filter signals, detect outliers, and express measurements with proper confidence intervals.

Published: March 5, 2026

probabilitystatisticsnoisefilteringmoving-averageapplied-mathengineering

Complex Numbers and Phasors

Complex numbers describe rotation, not imaginary things. Euler formula, phasors, impedance, and AC circuit analysis.

Published: March 4, 2026

complex-numbersphasorseuler-formulaimpedanceac-circuitsapplied-math

Linear Algebra: Vectors, Matrices, and Transforms

The language of engineering: how vectors and matrices describe forces, rotations, and systems of equations.

Published: March 3, 2026

linear-algebravectorsmatricestransformsapplied-mathengineering

Calculus for Engineers

The parts of calculus engineers actually use: derivatives, integrals, Taylor series, and the chain rule in real systems.

Published: March 2, 2026

calculusderivativesintegralstaylor-seriesapplied-mathengineering

Spherical Cows and the Art of Model Building

Why all models are wrong, some are useful, and how to build the right one for your problem.

Published: March 1, 2026

modelingsimulationapplied-mathengineeringabstraction
Modeling And Simulation

System Identification from Measured Data

Fit mathematical models to measured step response data using least squares estimation. Build a black-box model fitter that extracts transfer function parameters from noisy experimental data.

Published: March 9, 2026

system-identificationparameter-estimationleast-squarestransfer-functionstep-responsemodeling-simulation

Monte Carlo Methods for Engineering Decisions

Use random sampling to analyze tolerance stackups, predict manufacturing yield, and make quantitative engineering decisions when analytical solutions are impossible.

Published: March 8, 2026

monte-carlotolerance-analysisyieldstatistical-simulationengineering-decisionsmodeling-simulation

Simulating Signal Processing Pipelines

Design digital filters in Python, remove noise from sensor data, and export filter coefficients for embedded implementation. Build a noise filter designer with time-domain and frequency-domain analysis.

Published: March 7, 2026

signal-processingdigital-filtersbutterworthIIRFIRnoise-removalmodeling-simulation

Sensor Fusion and State Estimation

Combine noisy accelerometer and drifting gyroscope data into accurate orientation estimates using complementary and Kalman filters. Build an IMU orientation estimator in Python.

Published: March 6, 2026

sensor-fusionkalman-filtercomplementary-filterIMUstate-estimationmodeling-simulation

Control System Design in Simulation

Model a DC motor with inertia, friction, and back-EMF. Design and tune a PID controller in Python. Analyze overshoot, settling time, and steady-state error, then paste the gains into firmware.

Published: March 5, 2026

simulationPIDcontrol-systemsDC-motortuningstep-response

Thermal Modeling for Electronics

Build thermal resistance networks for electronic components. Simulate transient heat-up, size heatsinks, and determine whether your chip stays within its safe operating temperature.

Published: March 4, 2026

simulationthermalheatsinkelectronicstemperaturecooling

Mechanical System Dynamics

Model a spring-mass-damper system in Python. Sweep damping ratios, generate phase portraits, and build a suspension tuner that finds the optimal damping for minimum settling time.

Published: March 3, 2026

simulationmechanicalspring-mass-dampersuspensiondampingphase-portrait

Simulating Electrical Circuits

Build RC and RLC circuit simulators in Python. Generate step responses, verify time constants, sweep frequency for Bode plots, and compare results to oscilloscope measurements.

Published: March 2, 2026

simulationcircuitsRCRLCbode-plotfrequency-response

From Equations to Simulations

Set up the Python simulation workflow with SciPy solve_ivp. Model a lithium cell discharge curve and predict battery runtime under a realistic load profile.

Published: March 1, 2026

modelingsimulationpythonscipybatteryode

Contribution Stats

48
Authorship SSU
2024
Member Since
Kenya
Location
24
Education Contributions

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