You can find in this category all the public deliverables of the CrowdBot project that have been published so far.
This deliverable introduces the CrowdBot Challenge and presents its level of advancement before launching the first round. This document first presents the objective of the challenge, which is, in brief, to allow teams working in the field of crowd robot navigation to evaluate their navigation techniques and to compare their methods for moving robots in
Work package 5 (WP5) is about developing a coherent theoretical and functional system architecture that can accommodate the targeted scenarios and facilitate the integration of the different work packages across all three robotic platforms. However, this process must be iterative and reviewable after each milestone so that the achievement of such objectives is guaranteed during
Deliverable D1.3 is an updated version of D1.1. To enable the reader to have a complete understanding of the document without need to refer to previous ones, some existing portions have been reported here, even though they did not experiment a major update. To clarify things, for each section, a similar orange text box provides
In this deliverable we present the results of the first-round evaluations of all our crowdbots (Pepper, the smart wheelchair, cuyBot and Qolo). The evaluations are both quantitative and qualitative. They range from testing the efficacy of core components that are developed within the project and underpin the Crowdbots (e.g. sensing, localisation, simulation, planning), to fully
In this report we present our first prototype of the perception pipeline developed for the CROWDBOT project. Currently, the focus of the perception pipeline is on detecting and tracking pedestrians in low to medium density scenarios using RGB-D cameras and 2D LiDAR sensors. We begin with reviewing the major detection and tracking methods used in
The CrowdBot project’s crowd simulators perform two essential roles for the safe navigation of robots in populated environments: Crowd simulation for short-term prediction of the evolution of the situation of people in the vicinity of the robot. Crowd simulation for testing and evaluating the navigation functions of a robot in a densely populated environment. This
This report details the mapping, localisation and path planning solutions developed for the CROWDBOT project between months M1 to M20. Each of the three technical components have been designed with the explicit goal of achieving robot navigation in crowded environments, where many existing methods struggle due to the high degree of dynamic motion around the
This document aims at identifying risks that may arise when a robot navigates through a crowd and to provide a preliminary set of tools for identifying and evaluating potential physical hazards deriving from interaction with crowdbots. For the scope of this document, we define crowdbots as mobile robots operating in public, densely populated spaces, capable
As part of external stakeholder engagements, two types of experiments ─ user studies and robotic tests ─ are planned for the Crowdbot project. User studies are further classified as structured interviews and focus group engagements. Both user study experiments will be used to collect information and better understand the viewpoints and concerns of various stakeholders
Work package 5 (WP5) is about developing about a coherent theoretical and functional system architecture that can accommodate the targeted scenarios and facilitate the integration of the different work packages across all three robotic platforms. However, this process must be iterative and reviewable after each milestone so that the achievement of such objectives is guaranteed