Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

Authoring virtual crowds: a survey

Recent advancements in crowd simulation unravel a wide range of functionalities for virtual agents, delivering highly-realistic,natural virtual crowds. Such systems are of particular importance to a variety of applications in fields such as: entertainment(e.g., movies, computer games); architectural and urban planning; and simulations for sports and training. However, providingtheir capabilities to untrained users necessitates the development of authoring frameworks. Authoring virtual crowds is acomplex and multi-level task, varying from assuming control and assisting users to realise their creative intents, to deliveringintuitive and easy to use interfaces, facilitating such control. In this paper, we present a categorisation of the authorable crowdsimulation components, ranging from high-level behaviours and path-planning to local movements, as well as animation andvisualisation. We provide a review of the most relevant methods in each area, emphasising the amount and nature of influencethat the users have over the final result. Moreover, we discuss the currently available authoring tools (e.g., graphical userinterfaces, drag-and-drop), identifying the trends of early and recent work. Finally, we suggest promising directions for futureresearch that mainly stem from the rise of learning-based methods, and the need for a unified authoring framework.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska Curie grant agreement No 860768 (CLIPE project). This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital PolicyPeer ReviewedPostprint (author's final draft

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications