Recherche


Contents

Overall objectives

Origin of the project

Chroma is a bi-localized project-team at Inria Lyon and Inria Grenoble (in Auvergne-Rhône-Alpes region). The project was launched in 2015 before it became officially an Inria project-team on December 1st, 2017. It brings together experts in perception and decision-making for mobile robotics and intelligent transport, all of them sharing common approaches that mainly relate to the fields of Artificial Intelligence and Control. It was originally founded by members of the working group on robotics at CITI lab1, led by Prof. Olivier Simonin (INSA Lyon2), and members from Inria project-team eMotion (2002-2014), led by Christian Laugier, at Inria Grenoble. Academic members of the team are Olivier Simonin (Prof. INSA Lyon), Anne Spalanzani (Prof., UGA), Christian Laugier (Inria researcher emeritus, Grenoble), Agostino Martinelli (Inria researcher CR, Grenoble), Alessandro Renzaglia (Inria researcher CR, Lyon, since 2021) and Baudouin Saintyves (Inria researcher ISFP, Lyon, since 2024). Before joining the University of Groningen (NL) as Professor, Jilles Dibangoye was a member from 2015 to 2023 (as Asso. Prof. INSA Lyon). Christine Solnon (Prof. INSA Lyon) was also a member of the team from 2020 to 2024. Jacques Saraydaryan and Fabrice Jumel are two associate members as lecturer-researcher from CPE Lyon, since 2015.

The overall objective of Chroma is to address fundamental and open issues that lie at the intersection of the emerging research fields called “Human Centered Robotics” 3, “Multi-Robot Systems » 4, and AI for humanity.

More precisely, our goal is to design algorithms and models that allow autonomous agents to perceive, decide, learn, and finally adapt to their environment. A focus is given to unknown and human-populated environments, where robots or vehicles have to navigate and cooperate to fulfill complex tasks.

In this context, recent advances in embedded computational power, sensor and communication technologies, and miniaturized mechatronic systems, make the required technological breakthroughs possible.

Research themes

To address the mentioned challenges, we take advantage of recent advances in: probabilistic methods, machine learning, planning and optimization methods, multi-agent decision making, and swarm intelligence. We also draw inspiration from other disciplines such as Sociology, to take into account human models, or Physics/Biology, to design self-organized robots.

Chroma research is organized in two thematic axes : i) Perception and Situation Awareness ii) Decision Making. Next, we elaborate more about these axes.

  • Perception and Situation Awareness. This axis aims at understanding complex dynamic scenes, involving mobile objects and human beings, by exploiting prior knowledge and streams of perceptual data coming from various sensors. To this end, we investigate three complementary research problems:
  • Bayesian & AI based Perception: How to interpret in real-time a complex dynamic scene perceived using a set of different sensors, and how to predict the near future evolution of this dynamic scene and the related collision risks ? How to extract the semantic information and to process it for the autonomous navigation step.
  • Modeling and simulation of dynamic environments: How to model or learn the behavior of dynamic agents (pedestrians, cars, cyclists…) in order to better anticipate their trajectories?
  • Robust state estimation: Acquire a deep understanding on several sensor fusion problems and investigate their observability properties in the case of unknown inputs.

  • Decision making. This second axis aims to design algorithms and architectures that can achieve both scalability and quality for decision making in intelligent robotic systems and more generally for problem solving. Our methodology builds upon advantages of three (complementary) approaches: planning & control, machine learning, and swarm intelligence.
  • Planning under constraints: In this theme we study planning algorithms for a single or a fleet of mobile robots when they face complex and dynamics environments, i.e. populated by humans and/or mostly unknown. Approaches include heuristics and exact methods (eg. constraint programming).
  • Machine learning: We search for efficient and adaptive behaviours based on deep & reinforcement learning methods to solve complex single or multi-agent decision-making tasks.
  • Decentralized models: This theme explores decentralised algorithms and models for the control of multi-agent/multi-robot systems. In particular, we study swarm robotics for its ability to generate systems that are self-organising, robust and adaptive to perturbations.

Chroma is also concerned with applications and transfer of the scientific results. Our main applications include autonomous and connected vehicles, service robotics, exploration & mapping tasks with ground and aerial robots. Chroma is currently involved in several projects in collaboration with automobile companies (Renault, Toyota) and robotics compagnies such as Enchanted Tools (see Section 4).

The team has its own robotic platforms to support the experimentation activity (see5). In Grenoble, we have two experimental vehicles equipped with various sensors: a Toyota Lexus and a Renault Zoe; the Zoe car has been automated in December 2016. We have also developed two experimental test tracks respectively at Inria Grenoble (including connected roadside sensors and a controlled dummy pedestrian) and at IRT Nanoelec & CEA Grenoble (including a road intersection with traffic lights and several urban road equipments). In Lyon, we have a fleet of UAVs (Unmanned Aerial Vehicles) composed of 5 PX4 Vision, 3 IntelAero and 10 mini-UAVs Crazyflies (with a Lighthouse localization system). We have also a fleet of ground robots composed of 16 Turtlebot and 3 humanoids Pepper. These platforms are maintained and developed by contractual engineers and by SED engineers of the team.

Last activity report : 2024