The defense will take place on november 25 at 9 AM

Title
Learning spatial representations for single-task navigation and multi-task policies

Abstract
Autonomously behaving in the 3D world requires a large set of skills, among which are perceiving the surrounding environment, representing it precisely and efficiently enough to keep track of the past, making decisions, and acting to achieve specified goals. Animals, for instance humans, stand out by their robustness when it comes to acting in the
world. In particular, they can efficiently generalize to new environments but are also able to rapidly master many tasks of interest from a few examples. We will study how artificial neural networks can be trained to acquire a subset of these abilities. We will first focus on training neural agents to perform semantic mapping, both from augmented supervision signal and with proposed neural-based scene representations.
Neural agents are often trained with Reinforcement Learning (RL) from a sparse reward signal. Guiding the learning of scene mapping abilities by augmenting the vanilla RL supervision signal with auxiliary spatial reasoning tasks will help navigate efficiently. Instead of modifying the training signal of neural agents, we will also see how incorporating specific neural-based representations of semantics and geometry within the architecture of the agent can help improve performance in goal-driven navigation. Then, we will study how to explore a 3D environment to build neural representations of space that are as satisfying as possible based on robotic-oriented metrics we will propose. Finally, we will move from navigation-only to multi-task agents, and see how important it is to tailor visual features from
sensor observations to the task at hand to perform a wide variety of tasks, but also to adapt to new unknown tasks from a few demonstrations.

Jury
* Ivan Laptev, Directeur de Recherche (INRIA Paris / MBZUAI), Rapporteur
* Karteek Alahari, Directeur de Recherche (INRIA Grenoble), Rapporteur
* Nicolas Thome, Professeur des Universités (Sorbonne Université), Examinateur
* Georgia Chalvatzaki, Full Professor (TU Darmstadt), Examinatrice
* Laëtitia Matignon, Maître de Conférences (UCBL), Co-Directrice de thèse
* Olivier Simonin, Professeur des Universités (INSA Lyon), Co-Directeur de thèse
* Christian Wolf, Principal Scientist (Naver Labs Europe), Co-Directeur de thèse