Post-doctoral Research Visit F/m Postdoctoral

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**:
Every year Inria International Relations Department has a few postdoctoral positions in order to support Inria international collaborations. A postdoctoral position is opened within the Inria-KAIST partnership. It is part of the SHAARE associate team, initiated between the Auctus team at Inria and the IRiS lab at KAIST that 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.

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.

**Mission confiée**:
Lab contacts:
**Principales activités**:
Humans and robots can jointly perform a task in haptic teleoperation. The human operator remotely controls the robot while receiving feedback on the task environment. Such remote interaction is particularly beneficial in confined, unsafe, or sensitive environments such as hazardous sites, underwater or space. It 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 concepts have been proposed in the literature to transfer part of the task from the human to the robot. These approaches range from complementary and predefined subtask allocations to adaptive shared-control methods. Focusing on this second and more flexible paradigm, the postdoctoral project aims at improving shared control in haptic teleoperation.

To act as an effective collaborator, the robot should adapt its assistive behavior with respect to the human intent. The human inputs are first analyzed to infer the operator goal (such as the target object in pick-and-place) and consequently planned the robot assistive behavior. The authority level, that gives the impact of each agent on the action, is then fixed depending on some task-oriented criteria. The shared-autonomy approach combines the human motions and the robot assistive motions into a joint action, based on the authority distribution. A Model Predictive Shared Controller is developed at Auctus team [1] to compute the robot motion on a time horizon, given both the human and robot assistive trajectories. It generates a unified action, formulated as an optimization problem under robot and human limits and environmental constraints.

Two key aspects must be studied in our shared-autonomy approach to improve human-robot coordination and better share the task. According to their background and preferences, the postdoctoral scholar will work on these challenges:
1. Developing a method that dynamically adapts the authority level to better distribute the task between the human-robot agents. In conventional approaches the authority level is computed at each task state, as a function of task-oriented criteria (proximity to target [2]) or human-based indices (expertise [3], human activity [4]). The IriS lab has proposed a dynamic authority distribution method [4] that allocates the control authority in real-time from the energy produced in the human-robot interaction. This approach should be extended to a global optimization problem that capture task, human, environment factors to online shift the authority level.

2. Impro