AIBotPerson following by AI-based robot


  • Emmanuel BELLENGER (UPJV)

  • Yulin ZHANG (UPJV)

  • Javier CIVERA (University of Zaragoza)

  • Corentin LOCQUENEUX (UPJV)


This project aims to develop a new methodology for tracking people by mobile robots based on AI.The learning and repetition of trajectories in the field of robotics has developed over the ten last years. This has enabled a wider adoption of robots by society and facilitates human-robot collaboration.

Learning and repeating trajectories is one of the most relevant abilities for autonomous robots. It is the capacity of a robot to follow autonomously (repetition phase) a trajectory which was previously followed by another or the same robot but under human supervision (learning phase). Potential applications include, for example, surveillance robots, which must follow predefined trajectories with little variation.

The goal of this project is to develop algorithms to control robots in the learning phase in a more natural way for humans. More precisely, the human will create a path that the robot will have to repeat later. The teaching phase, during which the human will walk the trajectory, the robot will follow their movements in order to estimate movements and learn the trajectory.


The project is realized by the University Jules Verne Picardie in the Laboratory of Innovative Technologies(LTI) in collaboration with the Robotics, Perception and Real-Time group of the University of Zaragoza.

University of Jules Verne Picardie:

In LIT, we are interested in robotics and AI, and especially the experimentation of robots and robot constructions. The LIT of the University of Picardy Jules Verne (UPJV) is a multidisciplinary engineering and scientific laboratory that brings together its research on robotics, intelligent systems, Cloud computing and energy efficiency. The laboratory has 51 faculty members and is engaged in 7 national projects and 10 international projects.

The team participated in various research / industrial projects on the development of assisted robotics for the elderly and people with reduced mobility (ARAP Project), on the development of software based on an artificial neural network for the automatic segmentation of brain tumors (DAN BRAC project).

University of Zaragoza:

The Robotics, Perception and Real-Time group, one of the most important of the University of Zaragoza, was one of the pioneers in exploring the problem of Simultaneous, Localization and Mapping (SLAM), producing a flow of solid, continuous research and relevant transfers on the subject over the past two decades. Their members are the authors of many of the most cited articles in the field and several of the most downloaded open source SLAM visual codes. As authors and editors, they have an important visibility in the scientific and industrial community by being present in the largest conferences and journals of robotics and computer vision.