I build measurable robotics and engineering systems across SLAM, robot control, manipulation, computer vision, embedded electronics, and low-level systems.
My projects emphasize reproducibility, deterministic testing, explicit safety boundaries, and a strict separation between software/simulation evidence and physical hardware validation.
Live portfolio: vivek-vala-portfolio.vercel.app
| Project | Engineering focus | Evidence status |
|---|---|---|
| slam-robot-ros2 | ROS 2 SLAM, Gazebo ground truth, ATE/RPE, loop closure, rosbag regression, resource profiling | Static contracts + ROS Lyrical build CI verified; live Gazebo benchmark and hardware evidence remain gated |
| robotic-character-interface | Safety-governed embodied AI, motion authorization, firmware contracts, digital twin, telemetry, adversarial fault testing | Software-complete and simulation-validated; physical HIL validation pending |
| 3dof-robotic-arm | Analytic FK/IK, Cartesian planning, workspace/Jacobian analysis, servo calibration, Arduino control | Numerical/software validation in CI; physical endpoint accuracy pending |
| custom-pcb-motor-driver | DRV8848 dual motor-driver PCB, tolerance-aware current/thermal modeling, KiCad workflow, evidence gates | Analytical design evidence in CI; CAD/fabrication/bench evidence remain gated |
| http-server-from-scratch | C++20 HTTP/1.1 from raw sockets, secure static files, bounded concurrency, Linux epoll, reproducible benchmarks |
Linux + Windows CI verified; controlled-host M6B.2 performance evidence pending |
| Aurelia-Chan-Source | Cognitive runtime, DAG execution, durable persistence, verification contracts, persona/embodiment boundary | Deterministic five-run cognitive-cycle evidence in CI; production-scale and physical embodiment claims remain gated |
Autonomy / SLAM
↓
Safety-governed embodiment
↓
Manipulation / kinematics
↓
Embedded electronics / PCB
↓
Low-level systems engineering
↓
Cognitive runtime architecture
The goal is not to collect disconnected demos. Each flagship project demonstrates a different engineering layer while following the same evidence discipline.
- line-following-robot — control stack, PID behavior, corrected sensor-bar simulation geometry, regression testing, and robustness sweeps.
- cv-object-sorter — OpenCV perception → decision → actuation pipeline, passage-safe triggering, synthetic threshold-contract evidence, and labeled-image evaluation tooling.
- gesture-controlled-robot — MediaPipe gesture control with rotation-aware landmark geometry, temporal command stabilization, immediate STOP fail-safe, serial heartbeat, and MCU watchdog behavior.
| Area | Technologies |
|---|---|
| Robotics | ROS 2, SLAM, Gazebo, TF, localization, kinematics, trajectory evaluation |
| Computer vision | OpenCV, MediaPipe, HSV/contour pipelines, offline evaluation |
| Embedded systems | Arduino, servo control, PCA9685, serial protocols, watchdogs |
| Electronics | KiCad, PCB design workflow, motor drivers, electrical/current/thermal modeling |
| Systems | C++20, raw sockets, HTTP/1.1, Linux epoll, concurrency, benchmarking |
| Software | Python, FastAPI, Flask, SQLite, React, TypeScript, automated testing |
| Engineering workflow | Git, GitHub Actions, CI, machine-readable evidence, reproducible runbooks |
Simulation results stay simulation results. Analytical results stay analytical results. Physical claims require physical evidence.
Important experiments should preserve the exact commit, environment, configuration, raw artifacts, metrics, and failure cases so another developer can reproduce or challenge the result.
AI, perception, UI, and character layers should not directly command physical actuators. Motion authority belongs behind explicit planning, validation, safety supervision, and hardware boundaries.
Architecture, failure modes, limitations, evidence maturity, and release gates are treated as part of the engineering—not as afterthoughts.
- SLAM: execute and publish the first genuine Gazebo benchmark evidence bundle.
- vhttp: run the M6B.2 thread-pool vs
epollcampaign on a documented Linux/WSL2 host. - 3-DOF arm: add real endpoint-accuracy and repeatability measurements when physical hardware is available.
- Motor-driver PCB: progress from analytical/CAD validation to fabrication and bench evidence.
- RCI: replace engineering-predicted embodiment values with measured HIL/physical evidence when hardware exists.
- Aurelia: keep deterministic runtime evidence strong while avoiding unsupported AGI, production-scale, or physical-autonomy claims.
Robotics systems that are measurable, reproducible, safety-conscious, and honest about what has actually been demonstrated.