Diversity-aware social robots meet people: beyond context-aware embodied AI

The article introduces the concept of "diversity-aware" robotics and discusses the need to develop computational models to embed robots with diversity-awareness: that is, robots capable of adapting and re-configuring their behavior to recognize, respect, and value the uniqueness of the person they interact with to promote inclusion regardless of their age, race, gender, cognitive or physical capabilities, etc. Finally, the article discusses possible technical solutions based on Ontologies and Bayesian Networks, starting from previous experience with culturally competent robots.Comment: The article has been presented during the Roundtable "AI in holistic care and healing practices: the caring encounter beyond COVID-19", Anthropology, AI and the Future of Human Society, 6-10 June 2022, Royal Anthropological Institut

Path following and obstacle avoidance for an autonomous UAV using a depth camera

The main focus of this work is the development of a software architecture to autonomously navigate a flying vehicle in an indoor environment in presence of obstacles. The hardware platform used to test the developed algorithms is the AscTec Firefly equipped with a RGB-D camera (Microsoft Kinect): the sensor output is used to incrementally build a map of the environment and generate a collision-free path. Specifically, we introduce a novel approach to analytically compute the path in an efficient and effective manner. An initial path, given by the intersection of two 3D surfaces, is shaped around the obstacles by adding to either of the two surfaces a radial function at every obstacle location. The intersection between the deformed surfaces is guaranteed not to intersect obstacles, hence it is a safe path for the robot to follow. The entire computation runs on-board and the path is computed in real-time. In this article we present the developed algorithms, the software architecture as well as the results of our experiments, showing that the method can adapt in real time the robot's path in order to avoid several types of obstacles, while producing a map of the surroundings

The project PRISMA: Post-Disaster assessment with UAVs

In the context of emergency scenarios, Unmanned Aerial Vehicles (UAVs) are extremely important instruments, in particular during monitoring tasks and in relation to the Post-Disaster assessment phase. The current paper describes a summary of the work performed during PRISMA [1], a project focused on the development and deployment of robots and autonomous systems able to operate in emergency scenarios, with a specific reference to monitoring and real-time intervention. Among other aspects, the investigation of strategies for mapping and for path following, for the implementation of Human-Swarm Interfaces and for the coverage of large areas have been performed, and they will be here summarized

An Inverse Perspective Mapping Approach using Monocular Camera of Pepper Humanoid Robot to Determine the Position of Other Moving Robot in Plane

This article presents a method to know the position of object or moving robot in the plane while the camera is moving dynamically. An Inverse Perspective mapping (IPM) approach has been embedded in a monocular camera on Head of Pepper Humanoid Robot (Softbank Robotics) for real time position determination of other object or robot in plane. While the Pepper head is moving, it is difficult to determine position or distance to objects in front of the robot with any different degree of certainity. By applying IPM, a linear relationship between the IPM frame and world frame becomes the key element to know the position of object while the head is static but when the head orientation changes the IPM is modified to adapt the linear relationship between both frames. So, the proposed method is based on the extraction of accurate bird\u2019s-eye view. The method includes the Image Acquistion, IPM Filtering, Detection Phase, Region of Interest Selection and Pixel remapping

Modelling the influence of cultural information on vision-based human home activity recognition

Daily life activities, such as eating and sleeping, are deeply influenced by a person's culture, hence generating differences in the way a same activity is performed by individuals belonging to different cultures. We argue that taking cultural information into account can improve the performance of systems for the automated recognition of human activities. We propose four different solutions to the problem and present a system which uses a Naive Bayes model to associate cultural information with semantic information extracted from still images. Preliminary experiments with a dataset of images of individuals lying on the floor, sleeping on a futon and sleeping on a bed suggest that: i) solutions explicitly taking cultural information into account are more accurate than culture-unaware solutions; and ii) the proposed system is a promising starting point for the development of culture-aware Human Activity Recognition methods

Analysis of path following and obstacle avoidance for multiple wheeled robots in a shared workspace

The article presents the experimental evaluation of an integrated approach for path following and obstacle avoidance, implemented on wheeled robots. Wheeled robots are widely used in many different contexts, and they are usually required to operate in partial or total autonomy: in a wide range of situations, having the capability to follow a predetermined path and avoiding unexpected obstacles is extremely relevant. The basic requirement for an appropriate collision avoidance strategy is to sense or detect obstacles and make proper decisions when the obstacles are nearby. According to this rationale, the approach is based on the definition of the path to be followed as a curve on the plane expressed in its implicit form f(x, y) = 0, which is fed to a feedback controller for path following. Obstacles are modeled through Gaussian functions that modify the original function, generating a resulting safe path which - once again - is a curve on the plane expressed as f\u2032(x, y) = 0: the deformed path can be fed to the same feedback controller, thus guaranteeing convergence to the path while avoiding all obstacles. The features and performance of the proposed algorithm are confirmed by experiments in a crowded area with multiple unicycle-like robots and moving persons

Local Navigation Strategies for a Team of Robots

Whenever a mobile robot has to deal with an environment that is totally or partially unknown or dynamically changing, local navigation strategies are very important for the robot to successfully achieve its goals. Unfortunately, local navigation algorithms that have been proposed in the literature offer poor performance (or even fail) whenever the geometry of the free space in which the robot is requested to operate increases its complexity. In this paper, we deal with a team composed of many robots, and we show how robots navigating within an unknown environment with local communication capabilities (only line-of-sight communication is allowed) can cooperate by helping each other to achieve their own goals

A framework for culture-aware robots based on fuzzy logic

Cultural adaptation, i.e., the matching of a robot's behaviours to the cultural norms and preferences of its user, is a well known key requirement for the success of any assistive application. However, culture-dependent robot behaviours are often implicitly set by designers, thus not allowing for an easy and automatic adaptation to different cultures. This paper presents a method for the design of culture-aware robots, that can automatically adapt their behaviour to conform to a given culture. We propose a mapping from cultural factors to related parameters of robot behaviours which relies on linguistic variables to encode heterogeneous cultural factors in a uniform formalism, and on fuzzy rules to encode qualitative relations among multiple variables. We illustrate the approach in two practical case studies

Caring robots are here to help

Introducing Transcultural Robotic Nursin