Reproducibility challenges in robotic surgery.

Reproducibility of results is, in all research fields, the cornerstone of the scientific method and the minimum standard for assessing the value of scientific claims and conclusions drawn by other scientists. It requires a systematic approach and accurate description of the experimental procedure and data analysis, which allows other scientists to follow the steps described in the published work and obtain the "same results." In general and in different research contexts with "same" results, we mean different things. It can be almost identical measures in a fully deterministic experiment or "validation of a hypothesis" or statistically similar results in a non-deterministic context. Unfortunately, it has been shown by systematic meta-analysis studies that many findings in fields like psychology, sociology, medicine, and economics do not hold up when other researchers try to replicate them. Many scientific fields are experiencing what is generally referred to as a "reproducibility crisis," which undermines the trust in published results, imposes a thorough revision of the methodology in scientific research, and makes progress difficult. In general, the reproducibility of experiments is not a mainstream practice in artificial intelligence and robotics research. Surgical robotics is no exception. There is a need for developing new tools and putting in place a community effort to allow the transition to more reproducible research and hence faster progress in research. Reproducibility, replicability, and benchmarking (operational procedures for the assessment and comparison of research results) are made more complex for medical robotics and surgical systems, due to patenting, safety, and ethical issues. In this review paper, we selected 10 relevant published manuscripts on surgical robotics to analyze their clinical applicability and underline the problems related to reproducibility of the reported experiments, with the aim of finding possible solutions to the challenges that limit the translation of many scientific research studies into real-world applications and slow down research progress.

The GummiArm Project: A Replicable and Variable-Stiffness Robot Arm for Experiments on Embodied AI.

Robots used in research on Embodied AI often need to physically explore the world, to fail in the process, and to develop from such experiences. Most research robots are unfortunately too stiff to safely absorb impacts, too expensive to repair if broken repeatedly, and are never operated without the red kill-switch prominently displayed. The GummiArm Project was intended to be an open-source "soft" robot arm with human-inspired tendon actuation, sufficient dexterity for simple manipulation tasks, and with an eye on enabling easy replication of robotics experiments. The arm offers variable-stiffness and damped actuation, which lowers the potential for damage, and which enables new research opportunities in Embodied AI. The arm structure is printable on hobby-grade 3D printers for ease of manufacture, exploits stretchable composite tendons for robustness to impacts, and has a repair-cycle of minutes when something does break. The material cost of the arm is less than $6000, while the full set of structural parts, the ones most likely to break, can be printed with less than $20 worth of plastic filament. All this promotes a concurrent approach to the design of "brain" and "body," and can help increase productivity and reproducibility in Embodied AI research. In this work we describe the motivation for, and the development and application of, this 6 year project.

Site-selection criteria for the Einstein Telescope.

The Einstein Telescope (ET) is a proposed next-generation, underground gravitational-wave detector to be based in Europe. It will provide about an order of magnitude sensitivity increase with respect to the currently operating detectors and, also extend the observation band targeting frequencies as low as 3 Hz. One of the first decisions that needs to be made is about the future ET site following an in-depth site characterization. Site evaluation and selection is a complicated process, which takes into account science, financial, political, and socio-economic criteria. In this paper, we provide an overview of the site-selection criteria for ET, provide a formalism to evaluate the direct impact of environmental noise on ET sensitivity, and outline the necessary elements of a site-characterization campaign.

Trustable Environmental Monitoring by Means of Sensors Networks on Swarming Autonomous Marine Vessels and Distributed Ledger Technology.

The article describes a highly trustable environmental monitoring system employing a small scalable swarm of small-sized marine vessels equipped with compact sensors and intended for the monitoring of water resources and infrastructures. The technological foundation of the process which guarantees that any third party can not alter the samples taken by the robot swarm is based on the Robonomics platform. This platform provides encrypted decentralized technologies based on distributed ledger tools, and market mechanisms for organizing the work of heterogeneous multi-vendor cyber-physical systems when automated economical transactions are needed. A small swarm of robots follows the autonomous ship, which is in charge of maintaining the secure transactions. The swarm implements a version of Reynolds' Boids model based on the Belief Space Planning approach. The main contributions of our work consist of: (1) the deployment of a secure sample certification and logging platform based on the blockchain with a small-sized swarm of autonomous vessels performing maneuvers to measure chemical parameters of water in automatic mode; (2) the coordination of a leader-follower framework for the small platoon of robots by means of a Reynolds' Boids model based on a Belief Space Planning approach. In addition, the article describes the process of measuring the chemical parameters of water by using sensors located on the vessels. Both technology testing on experimental vessel and environmental measurements are detailed. The results have been obtained through real world experiments of an autonomous vessel, which was integrated as the "leader" into a mixed reality simulation of a swarm of simulated smaller vessels.The design of the experimental vessel physically deployed in the Volga river to demonstrate the practical viability of the proposed methods is shortly described.

Quantifying the evolutionary self-structuring of embodied cognitive networks.

We outline a possible theoretical framework for the quantitative modeling of networked embodied cognitive systems. We note that: (1) information self-structuring through sensory-motor coordination does not deterministically occur in ℝ(n) vector space, a generic multivariable space, but in SE(3), the group structure of the possible motions of a body in space; (2) it happens in a stochastic open-ended environment. These observations may simplify, at the price of a certain abstraction, the modeling and the design of self-organization processes based on the maximization of some informational measures, such as mutual information. Furthermore, by providing closed form or computationally lighter algorithms, it may significantly reduce the computational burden of their implementation. We propose a modeling framework that aims to give new tools for the design of networks of new artificial self-organizing, embodied, and intelligent agents and for the reverse engineering of natural networks. At this point, it represents largely a theoretical conjecture, and must still to be experimentally verified whether this model will be useful in practice.