Hugo T. M. Kussaba — accepted AI-conference papers

2026

Safe and Stable Neural Network Dynamical Systems for Robot Motion Planning

Allen Emmanuel Binny, Mahathi Anand, Hugo T. M. Kussaba, Lingyun Chen, Shreenabh Agrawal, Fares J. Abu-Dakka +1

RA-L 2026

Learning safe and stable robot motions from demonstrations remains a challenge, especially in complex, nonlinear tasks involving dynamic, obstacle-rich environments. In this paper, we propose Safe and Stable Neural Network Dynamical Systems S<inline-formula xmlns:mml="http://www.w3.org/1998/Math/Mat

Cited by 1 Source ↗code ↗Scholar ↗

2025

Scalable Learning of High-Dimensional Demonstrations with Composition of Linear Parameter Varying Dynamical Systems

Shreenabh Agrawal, Hugo T. M. Kussaba, Lingyun Chen, Allen Emmanuel Binny, Pushpak Jagtap, Sami Haddadin +1

IROS 2025

Learning from Demonstration (LfD) techniques enable robots to learn and generalize tasks from user demonstrations, eliminating the need for coding expertise among end-users. One established technique to implement LfD in robots is to encode demonstrations in a stable Dynamical System (DS). However, f

Cited by 1 Source ↗Scholar ↗

2024

Learning Barrier-Certified Polynomial Dynamical Systems for Obstacle Avoidance with Robots

Martin Schonger, Hugo T. M. Kussaba, Lingyun Chen, Luis Figueredo, Abdalla Swikir, Aude Billard +1

ICRA 2024poster

Established techniques that enable robots to learn from demonstrations are based on learning a stable dynamical system (DS). To increase the robots’ resilience to perturbations during tasks that involve static obstacle avoidance, we propose incorporating barrier certificates into an optimization pro…

Cited by 1 Source ↗code ↗Scholar ↗

2024

Optimal Control for Clutched-Elastic Robots: A Contact-Implicit Approach

Dennis Ossadnik, Vasilije Rakčević, Mehmet C. Yildirim, Edmundo Pozo Fortunić, Hugo T. M. Kussaba, Abdalla Swikir +1

ICRA 2024poster

Intrinsically elastic robots surpass their rigid counterparts in a range of different characteristics. By temporarily storing potential energy and subsequently converting it to kinetic energy, elastic robots are capable of highly dynamic motions even with limited motor power. However, the time-depen…

Cited by 1 Source ↗Scholar ↗

2022

BSA - Bi-Stiffness Actuation for optimally exploiting intrinsic compliance and inertial coupling effects in elastic joint robots

Dennis Ossadnik, Mehmet C. Yildirim, Fan Wu, Abdalla Swikir, Hugo T. M. Kussaba, Saeed Abdolshah +1

IROS 2022poster

Compliance in actuation has been exploited to generate highly dynamic maneuvers such as throwing that take advantage of the potential energy stored in joint springs. However, the energy storage and release could not be well-timed yet. On the contrary, for multi-link systems, the natural system dynam…

Cited by 4 Source ↗Scholar ↗