Autonomous robots deployed in shared human environments, such as agricultural settings, require rigorous safety assurance to meet both functional reliability and regulatory compliance. These systems must operate in dynamic, unstructured environments, interact safely with humans, and respond effectively to a wide range of potential hazards. This paper presents a verification workflow for the safety assurance of an autonomous agricultural robot, covering the entire development life-cycle, from concept study and design to runtime verification. The outlined methodology begins with a systematic hazard analysis and risk assessment to identify potential risks and derive corresponding safety requirements. A formal model of the safety controller is then developed to capture its behaviour and verify that the controller satisfies the specified safety properties with respect to these requirements. The proposed approach is demonstrated on a field robot operating in an agricultural setting. The results show that the methodology can be effectively used to verify safety-critical properties and facilitate the early identification of design issues, contributing to the development of safer robots and autonomous systems.

Dynamic Selection (DS), where base classifiers are chosen from a classifier's pool for each new instance at test time, has shown to be highly effective in pattern recognition. However, instability and redundancy in the classifier pools can impede computational efficiency and accuracy in dynamic ensemble selection. This paper introduces a meta-learning recommendation system (MLRS) to recommend the optimal pool generation scheme for DES methods tailored to individual datasets. The system employs a meta-model built from dataset meta-features to predict the most suitable pool generation scheme and DES method for a given dataset. Through an extensive experimental study encompassing 288 datasets, we demonstrate that this meta-learning recommendation system outperforms traditional fixed pool or DES method selection strategies, highlighting the efficacy of a meta-learning approach in refining DES method selection. The source code, datasets, and supplementary results can be found in this project's GitHub repository: https://github.com/Menelau/MLRS-PDS.

Dynamic Ensemble Selection (DES) is a Multiple Classifier Systems (MCS) approach that aims to select an ensemble for each query sample during the selection phase. Even with the proposal of several DES approaches, no particular DES technique is the best choice for different problems. Thus, we hypothesize that selecting the best DES approach per query instance can lead to better accuracy. To evaluate this idea, we introduce the Post-Selection Dynamic Ensemble Selection (PS-DES) approach, a post-selection scheme that evaluates ensembles selected by several DES techniques using different metrics. Experimental results show that using accuracy as a metric to select the ensembles, PS-DES performs better than individual DES techniques. PS-DES source code is available in a GitHub repository

America's meat processing crisis, mainly triggered by labor shortages and plant closings due to coronavirus spread, is set to unleash a new wave of automation across plants to ease labor and health woes. Bloomberg Law reports JBS SA, the world's largest meat producer, is preparing to install robots in slaughterhouses to mitigate the spread of COVID-19 among human employees working on the production line. JBS SA CFO Guilherme Cavalcanti recently said the Brazilian processing company expects to expand automation at its facilities across the world. Cavalcanti said the adoption of automation started before the pandemic as labor tightened at US plants due to a decline in immigration sparked by the Trump administration. He said labor shortages have developed in the US as the virus infects workers and shutters plants.

Where were you on the day of the world's first giant robot duel? Maybe you were working at your desk, brushing your teeth, labouring over your tax return, ironing the perfect pleat in tomorrow's pants. Meanwhile, giant robots were chainsawing other to shreds in a Japanese shed. SEE ALSO: Robotics expert Dr. Ross Mead reveals the truth about your favorite movie robots The world's first giant combat robot duel just happened on Tuesday, Oct. 17, pitting America and Japan against each other in a Twitch-livestreamed battle for the ages. Representing the United States, two epic robots from MegaBots Inc., founded by Matt Oehrlein and Gui Cavalcanti.

In 2015, two American engineers, Gui Cavalcanti and Matt Oehrlein, set out to build a giant human-piloted combat robot called Mk. II MegaBot that could drive on tank tracks and fire 3-pound projectiles. The robot was pretty cool, they thought, but who would they fight? So they decided to challenged the only other giant piloted robot in the world to a duel. That robot was a 4-metric-ton mech known as Kurata and built by Suidobashi Heavy Industry in Japan. The Japanese accepted the challenge.

Matt Oehrlein and Gui Cavalcanti, co-founders of the robotics company, MegaBots, with giant robots MK2 (left) and Eagle Prime. Matt Oehrlein and Gui Cavalcanti, co-founders of the robotics company, MegaBots, with giant robots MK2 (left) and Eagle Prime. Two years ago an American robotics company challenged a Japanese robotics company to a duel. This long-awaited match between the monstrous robots -- built by MegaBots Inc. of the U.S. and by Suidobashi Heavy Industry of Japan -- will be broadcast on Tuesday via the online steaming site, Twitch. It's billed as the "first ever giant robot fight." "This is a personal dream of mine come to life," says engineer Gui Cavalcanti, MegaBots' co-founder.

Who cares about a nuanced discussion comparing the necessity for big data-driven surveillance and the importance of privacy and strong encryption? What kind of puny, pencil-necked geek spends time pondering the relative pros and cons of logic-based artificial intelligence and statistical AI? If you're a red-blooded, testosterone-pumping tech fan who likes your gear served up with a thick-crusted slice of pro wrestling pageantry, the only confrontation that matters this year is the one pitting Californian robotics company MegaBots against Japanese robotics company Suidobashi in a totally awesome robot duel that's been years in the making. Set to finally take place this August (an announcement made this week), the date is the culmination of thousands of hours both companies have spent building giant human-driven mech robots -- you know, like those things out of Mobile Suit Gundam Wing. Now they're going to do what any self-respecting big kid would do when playing with kickass action figures: bash them against each other until a clear victor has emerged.