9 accepted papers
As robotic systems become increasingly complex, the need for explainable decision-making becomes critical. Existing explainability approaches in robotics typically either focus on individual modules, which can be difficult to query from the perspective of high-level behaviour, or employ monolithic a…
Robots and artificial intelligence technologies are becoming increasingly integrated into our daily lives. The introduction of humanoid robots into everyday settings is a gradual but ongoing process—one that society is already beginning to navigate. Yet this shift raises important questions: Who or
Accurate human motion prediction (HMP) is critical for seamless human-robot collaboration, particularly in handover tasks that require real-time adaptability. Despite the high accuracy of state-of-the-art models, their computational complexity limits practical deployment in real-world robotic applic
In this paper, we present an efficient and reliable deep-learning approach that allows users to communicate with robots via hand gesture recognition. Contrary to other works which use external devices such as gloves [1] or joysticks [2] to tele-operate robots, the proposed approach uses only visual
The collaboration between humans and robots in an object search task requires the achievement of shared plans obtained from communicating and negotiating. In this work, we assume that the robot computes, as a first step, a multi-agent plan for both itself and the human. Then, both plans are submitte…
The presented method implements a robot accompaniment in an adaptive side-by-side formation of a single person or a group of people. The method enhances our previous robot adaptive side-by-side behavior allowing the robot to accompany a group of people, not only one person. Adaptive means that the r
This paper presents a new method to allow robots to accompany a person or a group of people imitating pedestrians behavior. Two-people groups usually walk in a side-by-side formation and three-people groups walk in a V-formation so that they can see each other. For this reason, the proposed method c…
In this paper, we present a new method based on the Aerial Social Force Model (ASFM) to allow human-drone side-by-side social navigation in real environments. To tackle this problem, the present work proposes a new nonlinear-based approach using Neural Networks. To learn and test the rightness of th…
This paper presents a new model to make robots capable of approaching and engaging people with a human-like behavior, while they are walking in a side-by-side formation with a person. This method extends our previous work [1], which allows the robot to adapt its navigation behaviour according to the…