From Perception to Navigation in Environments with Persons: An Indoor Evaluation of the State of the Art.

Research in the field of social robotics is allowing service robots to operate in environments with people. In the aim of realizing the vision of humans and robots coexisting in the same environment, several solutions have been proposed to (1) perceive persons and objects in the immediate environment; (2) predict the movements of humans; as well as (3) plan the navigation in agreement with socially accepted rules. In this work, we discuss the different aspects related to social navigation in the context of our experience in an indoor environment. We describe state-of-the-art approaches and experiment with existing methods to analyze their performance in practice. From this study, we gather first-hand insights into the limitations of current solutions and identify possible research directions to address the open challenges. In particular, this paper focuses on topics related to perception at the hardware and application levels, including 2D and 3D sensors, geometric and mainly semantic mapping, the prediction of people trajectories (physics-, pattern- and planning-based), and social navigation (reactive and predictive) in indoor environments.

Localization System for Lightweight Unmanned Aerial Vehicles in Inspection Tasks.

This paper presents a localization system for Unmanned Aerial Vehicles (UAVs) especially designed to be used in infrastructure inspection, where the UAVs have to fly in challenging conditions, such as relatively high altitude (e.g., 15 m), eventually with poor or absent GNSS (Global Navigation Satellite System) signal reception, or the need for a BVLOS (Beyond Visual Line of Sight) operation in some periods. In addition, these infrastructure inspection applications impose the following requirements for the localization system: defect traceability, accuracy, reliability, and fault tolerance. Our system proposes a lightweight solution combining multiple stereo cameras with a robotic total station to comply with these requirements, providing full-state estimation (i.e., position, orientation, and linear and angular velocities) in a fixed and time-persistent reference frame. Moreover, the system can align and fuse all sensor measurements in real-time at high frequency. We have integrated this localization system in our aerial platform, and we have tested its performance for inspection in a real-world viaduct scenario, where the UAV has to operate with poor or absent GNSS signal at high altitude.

Decentralized 3D Collision Avoidance for Multiple UAVs in Outdoor Environments.

The use of multiple aerial vehicles for autonomous missions is turning into commonplace. In many of these applications, the Unmanned Aerial Vehicles (UAVs) have to cooperate and navigate in a shared airspace, becoming 3D collision avoidance a relevant issue. Outdoor scenarios impose additional challenges: (i) accurate positioning systems are costly; (ii) communication can be unreliable or delayed; and (iii) external conditions like wind gusts affect UAVs' maneuverability. In this paper, we present 3D-SWAP, a decentralized algorithm for 3D collision avoidance with multiple UAVs. 3D-SWAP operates reactively without high computational requirements and allows UAVs to integrate measurements from their local sensors with positions of other teammates within communication range. We tested 3D-SWAP with our team of custom-designed UAVs. First, we used a Software-In-The-Loop simulator for system integration and evaluation. Second, we run field experiments with up to three UAVs in an outdoor scenario with uncontrolled conditions (i.e., noisy positioning systems, wind gusts, etc). We report our results and our procedures for this field experimentation.

Decentralized sensor fusion for Ubiquitous Networking Robotics in Urban Areas.

In this article we explain the architecture for the environment and sensors that has been built for the European project URUS (Ubiquitous Networking Robotics in Urban Sites), a project whose objective is to develop an adaptable network robot architecture for cooperation between network robots and human beings and/or the environment in urban areas. The project goal is to deploy a team of robots in an urban area to give a set of services to a user community. This paper addresses the sensor architecture devised for URUS and the type of robots and sensors used, including environment sensors and sensors onboard the robots. Furthermore, we also explain how sensor fusion takes place to achieve urban outdoor execution of robotic services. Finally some results of the project related to the sensor network are highlighted.