Kenan Ahıska

E-mail

kahiska@metu.edu.tr

Department

Department of Electrical and Electronics Engineering

Positioning solution for heterogeneous swarm of UAVs and MAVs in 3D crowded environment Spanogianopoulos, Sotirios; Ahıska, Kenan (2025-04-01) Unmanned aerial vehicles (UAVs) and micro-aerial vehicles (MAVs) are becoming more popular in swarm applications due to their decreasing costs and wider availability. Swarm systems composed of different types of aerial veh...
A Transformer-Based Network for Full Object Pose Estimation with Depth Refinement Abdulsalam, Mahmoud; Ahıska, Kenan; Aouf, Nabil (2024-10-01) In response to increasing demand for robotics manipulation, accurate vision-based full pose estimation is essential. While convolutional neural networks-based approaches have been introduced, the quest for higher performan...
NDT RC: Normal Distribution Transform Occupancy 3D Mapping With Recentering Courtois, Hugo; Aouf, Nabil; Ahıska, Kenan; Cecotti, Marco (2024-01-01) TheNormal Distribution Transform Occupancy Map (NDT OM) is a mapping algorithm able to represent a dynamic 3D environment. The resulting map has fixed boundaries, thus a robot with unbounded displacement might fall outside...
Formation Solution for Heterogeneous Swarm of UAVs and MAVs in Crowded Environment Spanogianopoulos, Sotirios; Ahıska, Kenan (2024-01-01) Unmanned aerial vehicles (UAVs) and micro aerial vehicles (MAVs) gain more attraction in swarm applications as their cost reduces and their availability increases. Heterogeneous swarm solutions where these different types ...
A Novel Parameter Estimation Scheme for Vehicle Suspension Systems Based on Response and Test Track Prioritization Kanchwala, Husain; Ahıska, Kenan (2023-09-01) In this paper, a system identification methodology based on vehicle response and test track prioritization is presented. The proposed method can be used to perform time-domain parameter estimation by simply driving the veh...
A novel UAV-integrated deep network detection and relative position estimation approach for weeds Abdulsalam, Mahmoud; Ahıska, Kenan; Aouf, Nabil (2023-08-01) This paper aims at presenting a novel monocular vision-based approach for drones to detect multiple type of weeds and estimate their positions autonomously for precision agriculture applications. The methodology is based o...
Robust Multispectral Visual-Inertial Navigation With Visual Odometry Failure Recovery Beauvisage, Axel; Ahıska, Kenan; Aouf, Nabil (2022-07-01) Besides the large amount of information multi-spectral imaging offers, multispectral visual odometry remains overlooked due to the dissimilarity between modalities. In order to tackle the challenging feature matching betwe...
OAST: Obstacle Avoidance System for Teleoperation of UAVs Courtois, Hugo; Aouf, Nabil; Ahıska, Kenan; Cecotti, Marco (2022-04-01) This article presents a novel flight assistance system, obstacle avoidance system for teleoperation (OAST), whose main role is to make teleoperation of small multirotor unmanned aerial vehicles (UAVs) safer and more effici...
RRT-based Path Planning for Car-Like Vehicles with Nonholonomic Constraints Spanogianopoulos, Sotirios; Sirlantzis, Konstantinos; Ahıska, Kenan (2022-01-01) In this paper, for car-like mobile robots, a novel path planning algorithm is proposed. The algorithm is based on rapidly-exploring random trees (RRT) with fixed nodes (RRT*FN). An improvement on the RRT*FN is proposed to ...
A Comparison of Trajectory Planning and Control Frameworks for Cooperative Autonomous Driving Viana, Icaro Bezerra; Kanchwala, Husain; Ahıska, Kenan; Aouf, Nabil (2021-07-01) This work considers the cooperative trajectory-planning problem along a double lane change scenario for autonomous driving. In this paper, we develop two frameworks to solve this problem based on distributed model predicti...

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