Available October 2026

Batchaya Yacynte -
Perception engineer.

Building the vision systems that let machines navigate when GPS fails. M.Eng. AI Engineering & Autonomous Systems · TH Ingolstadt · Airbus Helicopters consortium.

See my work ↓ IEEE Publication ↗
Batchaya Yacynte
4+
Years building
perception systems
~10cm
Lateral accuracy
Project ENGEL
1st
Author IEEE publication
REM 2024
3
Real hardware platforms
validated outdoors

Affiliated with

TH Ingolstadt - M.Eng. Airbus Helicopters Consortium Fraunhofer IVI AIMotion Bavaria IEEE REM 2024 - First Author

About

Engineer, researcher,
builder.

I'm a Cameroonian robotics engineer based in Ingolstadt, Germany. My work lives at the boundary where computer vision, probabilistic estimation, and control systems meet, building perception pipelines that have to perform on real hardware, outdoors, under pressure.

My master's thesis, developed within an Airbus Helicopters consortium, delivers closed-loop GPS-denied UAV repositioning with ~10 cm lateral accuracy and ~0.1° heading precision in under 30 seconds, validated in both clear and rainy simulation, using only an onboard monocular camera. Before that, at Fraunhofer IVI, I designed an event-based optical flow system for Time-to-Collision estimation that outperformed three state-of-the-art methods on the MVSEC benchmark, running single-threaded on NVIDIA Jetson.

I care about systems that work outside the lab. My work is validated on KITTI, EuRoC, custom DJI Tello flights with OptiTrack ground truth, and live outdoor field tests, not just in simulation.

Selected work

Projects that ship.

Real-world perception systems, embedded deployments, and autonomous platforms, from Airbus-consortium UAVs to Fraunhofer agricultural robotics.

01
Master's Thesis Airbus Helicopters Consortium · AIMotion Bavaria 2025 – 2026
Project ENGEL: Vision-Based GPS-Denied UAV Repositioning
Real-time monocular pipeline for autonomous helicopter landing in GPS-denied environments. Built the Unreal Engine 5 validation environment, including a continuous image stream, UDP-based UAV control, and simulated weather effects such as rain and snow for repeatable testing. SuperPoint + LightGlue feature matching feeds PNEC pose recovery; the resulting pose drives a sigmoid-mapped velocity controller in a closed loop. Developed ONNX-exportable SuperPoint and LightGlue inference pipelines for deployment across different devices. Validated in UE5 simulation under clear and adverse-weather scenarios; outdoor flight validation ongoing.
~10 cm lateral accuracy ~0.1° heading accuracy Converges in <30 s >98% image similarity Clear + rainy sky validated
Project ENGEL UAV repositioning Project ENGEL simulation Project ENGEL validation environment
ENGEL · simulation
↗
02
Research · KoSiNuS Fraunhofer IVI Apr 2025 – Mar 2026
Event-Based Optical Flow for Real-Time TTC Estimation
Probabilistic event-based optical flow pipeline for Time-to-Collision estimation in safety-critical agricultural autonomy. Gaussian residual model with motion-adaptive variance scaling and affine RANSAC outlier rejection, integrated into ROS2 with an IDS uEye DVS sensor on NVIDIA Jetson embedded hardware.
2.33 px AEPE Outperforms UnFlow, EV-FlowNet, Shiba et al. 3.5 Meps single-threaded on Jetson Orin
optical Flow estimation
Kosinus · Event Flow
–
03
Personal Project Custom UAV Build
Autonomous Surface Area Mapping Drone
Designed and hand-built a custom ~25×25 cm UAV (Betaflight F405 V3 + Radxa A7A) and developed a full stereo vision pipeline for autonomous land surface area measurement. Targets agricultural and surveying use cases as a low-cost alternative to total stations. Full pipeline from stereo depth estimation to contour detection and geometric area computation, generating topographic and plat map outputs.
KITTI validated Topographic + plat map outputs Custom hardware build
Bettle dron Project ENGEL UAV repositioning Project ENGEL simulation Project ENGEL validation environment
Bettle · Maps
–
04
Course Project Grade 1.0 2025 – 2026
Deep Visual-Inertial Odometry Pipeline
End-to-end deep learning VIO system for GPS-free 6-DoF localization, fusing monocular camera and IMU measurements with CNNs. Evaluated on EuRoC MAV for indoor flight and KITTI for outdoor driving scenarios.
0.038 m ATE — EuRoC MAV 1.42 m ATE — KITTI
Deep visual inertial odometry result VIO trajectory Deep visual inertial odometry result VIO trajectory
Monocular · VIO · Learning
–
05
Robotics Engineering CAD & Mechatronics Personal / Industrial
Robotic Systems & Mechanical Design
Mechanical and mechatronic engineering projects spanning robotic systems, CAD design, vehicle assembly-line concepts, and agricultural robotics. Designed mechanical assemblies and integrated them with electronics, actuators, sensing, and autonomous control concepts.
CAD design Robotic assemblies Agricultural robotics Mechatronic systems
Robotic CAD design Mechanical assembly CAD Agricultural robot Agricultural robot
Robotics · CAD
↗
06
Bachelor's Thesis IEEE REM 2024 · First Author 2022 – 2024
Monocular Visual-Inertial Odometry for GPS-Free Drone Navigation
Sparse optical flow VIO pipeline for autonomous drone navigation without external positioning. RANSAC-based outlier rejection and camera-IMU calibration. Validated across KITTI benchmark, DJI Tello flights with OptiTrack ground truth, and Unreal Engine simulation.
0.94% translation RMSE/m — KITTI 5.32% — DJI Tello real flight 0.015 deg/m rotation error
Simulation result 3D Translation result Tello flight Optical flow
Monocular · VIO · Geometry
↗

Publication

Peer-reviewed research.

IEEE REM 2024 · First Author · DOI: 10.1109/REM63063.2024.10735689
Getting Started With a Simple Visual-Inertial Odometry
Batchaya, Y. D. et al. — Presented at IEEE REM 2024 · Published in IEEE Xplore
DOI 10.1109/REM63063.2024.10735689
IEEE Xplore ↗

Contact

Let's build
something real.

Looking for robotics and computer vision roles in Germany starting September 2026. If you work on autonomous systems, UAVs, or embedded perception — let's talk.

Email batchaya.yacynte@gmail.com → LinkedIn linkedin.com/in/batchaya-yacynte → GitHub github.com/Yacynte → Publication IEEE REM 2024 · DOI 10.1109/REM63063.2024.10735689 →