Hacettepe University Robotics Laboratory

Robots that learn.Intelligence that moves.

We build learning-enabled robotic systems that perceive, reason and act in complex real-world environments.

Explore our researchSelected publications
6Research directions
9Researchers & alumni
AnkaraHacettepe University
Portrait of the HURLAB director
Research

Embodied intelligence, from perception to action.

HURLAB investigates how robots can build useful representations of the world, make decisions under uncertainty and learn robust behaviors from data, models and interaction.

01

Robot Learning

Imitation learning, reinforcement learning, model-based learning and generalist robot policies.

02

Autonomous Systems

Decision-making, motion understanding and reliable autonomy in dynamic environments.

03

Robot Perception

Multimodal sensing with cameras, RGB-D and LiDAR for semantic scene understanding.

04

Localization & SLAM

Place recognition, topological mapping and long-term spatial representations.

05

Computer Vision

Segmentation, detection, object pose estimation and 3D environment understanding.

06

Human-Robot Interaction

Gesture understanding, collaborative robotics and learning grounded actions from people.

People

A focused team with a broad robotics perspective.

HURLAB brings together faculty collaborators and graduate researchers working across artificial intelligence, computer vision and robotics.

Aİ

Ahmet İnanç

PhD Candidate

HM

Hatice Meltem Nergis

PhD Candidate

AA

Aysu Aylin Kaplan

MSc Student

HA

Hüseyin Arslan

MSc Student

AD

Ayşema Dilara Kılıç

MSc Student

EC

Emre Canitez

MSc Alumnus

SE

Seran Erdemir

MSc Alumna

Publications

Selected recent work.

Research on multimodal road understanding, semantic grid prediction, trajectory forecasting and perception for autonomous systems.

2023

Multi-Modal Multi-Task (3MT) Road Segmentation

E. Milli, Ö. Erkent and A. E. Yılmaz

IEEE RA-L
2023

LAPTNet-FPN: Multi-scale LiDAR-aided Projective Transform Network for Real-Time Semantic Grid Prediction

M. Diaz-Zapata, D. Sierra-Gonzalez, Ö. Erkent, C. Laugier and J. Dibangoye

ICRA
2022

MultiLane: Lane Intention Prediction and Sensible Lane-Oriented Trajectory Forecasting on Centerline Graphs

D. Sierra González, A. Paigwar, Ö. Erkent and C. Laugier

ITSC
2022

TransFuseGrid: Transformer-based LiDAR-RGB Fusion for Semantic Grid Prediction

G. Salazar-Gomez et al.

ICARCV
2022

LAPTNet: LiDAR-Aided Perspective Transform Network

M. Diaz-Zapata, Ö. Erkent, C. Laugier, J. Dibangoye and D. Sierra-Gonzalez

ICARCV
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