Boundedness approach to gait planning for the flexible linear inverted pendulum model

In this paper, we take advantage of the Flexible LIP model that has shown to be more realistic w.r.t. the LIP for cost-eective or compliant biped robots for gait generation. We can use a stable inversion approach to obtain bounded Center of Mass (CoM) reference trajectories and show several advantages compared to preview control: avoidance of integration, lower computation time, exact tracking of reference Zero Moment Point (ZMP) trajectories and Capture Point determination

A.: Extending virtual robots towards robocup soccer simulation and @home

Abstract. The RoboCup is an initiative to promote the development of robotics in a social relevant way. The competition consists of several leagues and it would be beneficial if developments in one league could be reused in other leagues. This paper describes the development of a simulation model for a humanoid robot inside USARSim, which could be the basis of synergy between the Rescue Simulation, Soccer Simulation and @Home League. USARSim is an existing 3D simulator based on the Unreal Engine, which provides facilities for good quality rendering, physics simulation, networking, a highly versatile scripting language and a powerful visual editor. This simulator is now extended with the dynamics of a walking robot and validated for the humanoid robot Nao. On this basis many other robotic applications as benchmarked in the RoboCup initiative become possible

Artificial intelligence for hospital health care: Application cases and answers to challenges in european hospitals

The development and implementation of artificial intelligence (AI) applications in health care contexts is a concurrent research and management question. Especially for hospitals, the expectations regarding improved efficiency and effectiveness by the introduction of novel AI applications are huge. However, experiences with real-life AI use cases are still scarce. As a first step towards structuring and comparing such experiences, this paper is presenting a comparative approach from nine European hospitals and eleven different use cases with possible application areas and benefits of hospital AI technologies. This is structured as a current review and opinion article from a diverse range of researchers and health care professionals. This contributes to important improvement options also for pandemic crises challenges, e.g., the current COVID-19 situation. The expected advantages as well as challenges regarding data protection, privacy, or human acceptance are re-ported. Altogether, the diversity of application cases is a core characteristic of AI applications in hospitals, and this requires a specific approach for successful implementation in the health care sector. This can include specialized solutions for hospitals regarding human–computer interaction, data management, and communication in AI implementation projects. © 2021 by the authors. Licensee MDPI, Basel, Switzerland