Ajay Suresha Sathya
KU Leuven, Flanders Make (Belgium), Université Paris Sciences et Lettres
Papers
10
Total Citations
181
H-Index
5
About
Ajay Suresha Sathya is a robotics and control researcher whose work sits at the intersection of optimal control, real-time motion planning, and robot dynamics. His research has made significant contributions to nonlinear model predictive control (NMPC) and trajectory optimization, with a particular focus on making these computationally demanding techniques practical for real-world robotic systems. His most influential work, "Embedded Nonlinear Model Predictive Control for Obstacle Avoidance Using PANOC" (2018, 98 citations), introduced a novel modeling framework for handling nonconvex obstacles — including polytopes and ellipsoids — enabling real-time obstacle avoidance on embedded hardware. He further extended this line of work to robot arm motion planning and developed FATROP (2023, 29 citations), a high-performance solver that exploits optimal control problem structure to achieve significantly faster trajectory optimization than general-purpose solvers. His contributions also span constrained rigid-body dynamics algorithms, hierarchical task specification for redundant robots, and open-source tooling through the Tasho Python toolbox, which streamlines deployment of OCP-based robot motion skills. Across his portfolio, Sathya consistently bridges theoretical rigor with engineering practicality, helping bring advanced optimization-based control within reach of real-time robotic applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6Constrained Articulated Body Dynamics Algorithms5 citations · 2024
- 7
- 8
- 9
- 10