Sensor fusion

SLAM

Computer vision

The Python code controls the robots, conveyers, and other automation pipelines, and works in both simulation and on physical hardware.

Interacted with clients to customize the software to their needs.

Led the effort to cloudify the Python development pipeline and expand its capabilities so it can handle multi-files and multi-processes. This expands the capabilities of the Python pipeline.

Develop and maintain the localization and mapping algorithms for a

Develop and maintain calibration algorithms

Setup an OptiTrack system that can be used for performance evaluations

The primary tools used in this job are ROS, C++, Python, and nonlinear least squares (mainly using Ceres)

Lie groups (e.g., SE(3) and SE_2(3)) to model the kinematics of the robot;

Statistical inference (to derive the probabilistic equations);

Invariant extended Kalman filtering;

Optimization on manifolds;

Linear matrix inequalities (LMIs) (semi-definite programming);

Sensor modelling;

MATLAB;

GTSAM (package to solve SLAM problems using efficient graphical approaches);

ManOpt (MATLAB package for optimization on manifolds);

YALMIP, MOSEK, SDPT3 (MATLAB semidefinite programming packages).

outlining the test procedures and protocols

writing test reports

CAD designing using Autodesk Inventor

3D printing

programming the testing platform using Python

Designing jigs (CNC and metal bending)