Phd Position F/m Hardware Acceleration for Unmanned Aerial Vehicle Control Algorithms

Le descriptif de l’offre ci-dessous est en Anglais_

**Type de contrat**: CDD

**Niveau de diplôme exigé**: Bac + 5 ou équivalent

**Fonction**: Doctorant

**A propos du centre ou de la direction fonctionnelle**:
The Inria Rennes - Bretagne Atlantique Centre is one of Inria's eight centres and has more than thirty research teams. The Inria Center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.

**Contexte et atouts du poste**:
**Disclaimer**

**A PhD is not** a continuation of coursework or a natural next step after a Master’s degree. **A PhD is** a long-term, research-focused **commitment** that requires deep **curiosity**, **self-motivation**, **resilience**, and a certain degree of **autonomy**.

**Context & background**:
Robots are physical agents that interact with their physical environment. Accordingly, their sensorimotor capabilities are essential and largely determine the activities that robots can perform. In recent years, great progress has been made in sensory capabilities thanks to significant advances in machine learning and dedicated hardware. In contrast, much less progress has been made in motor skills. Examples of promising approaches in the current scientific literature are Model Predictive Control (MPC) [1] and Model Predictive Path Integral (MPPI) control [2], where control actions are optimized over a finite time horizon, considering the time evolution of robot dynamics to optimize a given cost or reward function that describes the robot motion. Such algorithms are particularly suited for **optimizing control trajectories and** **planning horizons** **in real time** due to their ability to handle dynamic environments.

From a control perspective, **planning a horizon that is as long as possible** to manage complex trajectories while considering the environment is essential. Additionally, maintaining **a high control frequency** is crucial to meet the **real-time** demands imposed by real-world physics and, if necessary, to adjust the sequence of movements. In the **resource-constrained context of** **small-scale UAVs**, such control algorithms are crucial as they enable **optimal trajectory generation and real-time decision-making** in complex, dynamic, and uncertain environments. However, particularly for **battery-powered UAVs**, achieving a high control frequency while planning for a long horizon is difficult due to limited computational power and energy constraints [3], and conventional GPU acceleration often requires excessive energy consumption.

In recent years, **hardware acceleration** [4] has become increasingly popular, using **dedicated platforms** such as **FPGAs** (Field Programmable Gate Arrays) and **ASICs** (Application-specific Integrated Circuits)**,** increasing energy efficiency by **orders of magnitude** [5]. However, **dedicated hardware acceleration for small-scale UAV control has not been proposed**.

The PhD is in collaboration between the computer architecture team (TARAN) and the robotics team (RAINBOW) at Inria Centre at Rennes University.

Contact people:
[1] E. F. Camacho and C. Bordons, Model Predictive control. in Advanced Textbooks in Control and Signal Processing. London: Springer, 2007. doi: 10.1007/978-0-85729-398-5.
[2] G. Williams, P. Drews, B. Goldfain, J. M. Rehg, and E. A. Theodorou, “Aggressive driving with model predictive path integral control,” in 2016 IEEE International Conference on Robotics and Automation (ICRA), May 2016, pp. 1433-1440. doi: 10.1109/ICRA.2016.7487277.
[3] K. Nguyen, S. Schoedel, A. Alavilli, B. Plancher, and Z. Manchester, “TinyMPC: Model-Predictive Control on Resource-Constrained Microcontrollers,” in 2024 IEEE International Conference on Robotics and Automation (ICRA), May 2024, pp. 1-7. doi: 10.1109/ICRA57147.2024.10610987.
[4] W. J. Dally, Y. Turakhia, and S. Han, “Domain-specific hardware accelerators,” Commun ACM, vol. 63, no. 7, pp. 48-57, Jun. 2020, doi: 10.1145/3361682
[5] J. L. Hennessy and D. A. Patterson, “A new golden age for computer architecture,” Commun ACM, vol. 62, no. 2, pp. 48-60, Jan. 2019, doi: 10.1145/3282307.

**Mission confiée**:
**Principales activités**:
**Compétences**:
**Required technical skills**:

- Good knowledge of **computer architectures** and **embedded systems**:

- **HW design**: VHDL/Verilog basics, HW synthesis flow
- **Programming**knowledge (C/C++, python)
- Experience in **HW/SW co-design** and **robotics** is a plus

**Languages**: proficiency in written English and fluency in spoken English are required.

**Other**values appreciated are** open-mindedness, strong integration skills, and team spirit.

**Avantages**:
- Subsidized meals
- Partial reimbursement of public transport costs
- Possibility of teleworking (90 days p