Post-doctoral Research Visit F/m Postdoctoral Research Position

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

**Type de contrat**: CDD

**Niveau de diplôme exigé**: Thèse ou équivalent

**Fonction**: Post-Doctorant

**A propos du centre ou de la direction fonctionnelle**:
The Inria center at the University of Bordeaux is one of the nine Inria centers in France and has about twenty research teams.. The Inria centre 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 SMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute...

**Contexte et atouts du poste**:
About the centres

The **Inria center of the University of Bordeaux** is a public scientific institute located in Talence (France). It gathers together about twenty research teams in digital sciences, computer sciences, mathematics, robotics, and machine learning, with different academic and industrial partners.

**KAIST**, also known as the Korea Advanced Institute of Science and Technology, is a public research university located in Daejeon, South Korea. It is considered one of the top universities in Korea and is renowned for its excellence in science, engineering, and technology. The research areas at KAIST cover a wide range of fields, including physics, chemistry, materials science, engineering, computer science, and biology. The university has a particular strength in artificial intelligence and robotics, with world-class research teams in these areas.

Context

Every year Inria International Relations Department has a few postdoctoral positions **in order to support Inria international collaborations**.

The postdoctoral contract will have a duration of **12 to 24 months**. The default start date is **November 1st, 2025 and not later than January, 1st 2026**. The postdoctoral fellow will be recruited by the Inria center of the University of Bordeaux (Auctus team) in France, but the project time will be **shared between France and**South Korea**, with exchange periods at KAIST (IRiS lab) to share the works and progresses (please note that the postdoctoral fellow has to start his/her contract being in France and that the visits have to respect Inria rules for missions).

The proposed postdoctoral project is part of the Inria-KAIST partnership, and specifically of the **SHAARE associate team**, initiated between the **Auctus** team at Inria and the **I**R**iS** lab at KAIST. The associate team focuses on **haptics and shared teleoperation**. Together, we aim at developing **shared-control approaches** that, either, better guide the human through adaptive haptic guidance, or adjust the robot behavior according to the human gestures.

**Mission confiée**:
**Principales activités**:
Humans can perform remote tasks in haptic teleoperation of a robot, which is particularly beneficial in confined, unsafe, or sensitive environments such as hazardous sites, underwater or space. This interaction modality naturally combines human high-level intelligence and robot physical capabilities while maintaining the safety and comfort required for the Human. Unfortunately, conventional teleoperation methods do not leverage the robot assistance and collaborative ability to its fullest, since the operator fully controls the remote task, with a high mental workload and poor performances.

Recent shared-autonomy controllers have been proposed in the literature to transfer part of the task from the human to an automatic execution by the robot. These approaches range from complementary and predefined sub-task allocations to **adaptive shared-control methods** [1]. Focusing on this second paradigm, an important challenge lies in how the control input of the robot is shared between human control and some assistance. The human motion is usually analyzed to infer the operator goal (such as the target object in a pick-and-place task) and consequently plan the robot assistance. While the assistance tries to predict the intent and adapt to the human actions, the human and assistance behaviors may differ due to their own physical capabilities, different task strategies, or incomplete models of the environment. Therefore, we want the resulting robot behavior to minimize the conflicts between the human and the assistance.

In the shared control community, this problem is described as an **arbitration problem**, which consists in correctly adjusting the level of control authority between the human and the assistance. The authority level defines the influence of each agent on the shared action. In conventional approaches, it is computed as a function of some task-oriented criteria (e.g. proximity to target [2]) or human-based metrics (expertise [3], human activity [4]). This postdoctoral project aims at developing **methods that dynamically adapt the authority level during the activity**, as the human may need to take over the assistance, for example whe