Papers
9
Total Citations
75
H-Index
4
About
Ahmad Hably is a researcher whose work sits at the intersection of autonomous robotics, control theory, and multi-agent systems. His most significant contributions center on applying Nonlinear Model Predictive Control (NMPC) to complex robotic challenges, particularly pursuit-evasion games involving nonholonomic mobile robots. His 2020 study on pursuit-evasion for ground robots with obstacle avoidance has garnered 22 citations, establishing him as a notable voice in competitive game-theoretic robotics. Building on this, his 2021 work on game-theoretic and MPC-based algorithms for non-cooperative games (17 citations) and dynamic obstacle avoidance (15 citations) further cemented his expertise in real-time autonomous decision-making under uncertainty. Hably's research extends beyond ground robotics into aerial systems, including quadrotor control enhanced by neural networks and event-based learning, as well as distributed finite-time coverage control for multi-quadrotor swarms. A particularly imaginative project, STRAD, explores suspended aerial manipulators designed to create large-scale street art — a testament to his creative application of robotic systems. With roots in bounded control approaches for drones dating back to his 2007 doctoral work, Hably has built a coherent and expanding research vision bridging theoretical control frameworks with real-world autonomous robot deployment.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Dynamic Obstacles Avoidance Using Nonlinear Model Predictive Control15 citations · 2021
- 4
- 5Design of a Suspended Manipulator With Aerial Elliptic Winding4 citations · 2024
- 6Neural Enhanced Control for Quadrotor Linear Behavior Fitting3 citations · 2022
- 7Event-based neural learning for quadrotor control3 citations · 2023
- 8
- 9Approches bornées pour la commande des drones2 citations · 2007