We consider a service robot that offers chocolate treats to people passing in its proximity: it has the capability of predicting in advance a person's intention to interact, and to actuate an "offering" gesture, subtly extending the tray of chocolates towards a given target. We run the system for more than 5 hours across 3 days and two different crowded public locations; the system implements three possible behaviors that are randomly toggled every few minutes: passive (e.g. never performing the offering gesture); or active, triggered by either a naive distance-based rule, or a smart approach that relies on various behavioral cues of the user. We collect a real-world dataset that includes information on 1777 users with several spontaneous human-robot interactions and study the influence of robot actions on people's behavior. Our comprehensive analysis suggests that users are more prone to engage with the robot when it proactively starts the interaction. We release the dataset and provide insights to make our work reproducible for the community. Also, we report qualitative observations collected during the acquisition campaign and identify future challenges and research directions in the domain of social human-robot interaction.

As in any other manufacturing process, robotics and automation are already greatly involved in injection molding and bring considerable benefits to the table. According to statistics released by the European Plastics Machinery Organization EUROMAP, the number of sold injection molding machines equipped with robots rose from 18% in 2010 to almost a third of all injection machines sold with 32% by the first quarter of 2019. There is definitely a change in attitude in this trend, with a respectable number of plastic injection molders embracing robots to get ahead of their competition. Undoubtedly, there has been a serious upwards trend towards the use of robotics and automation in plastics processing. A significant part of this is driven by the demand for more flexible solutions, as the 6-axis industrial robots in precision molding, for example, are certainly more common nowadays than several years before.

We can bring analytics students into this to figure the best way to analyze the environmental data,

Low birth rates and higher life expectancies mean that those over 65 years old now will account for 28.7 % of Europe's population by 2080, according to Eurostat, the EU's statistics arm. It means the age-dependency ratio – the proportion of the elderly compared with the number of workers – will almost double from 28.8 % in 2015 to 51 % in 2080, straining healthcare systems and national budgets. Yet there's hope marching over the horizon, in the form of robots. The creators of one humanoid robot under development for the elderly say it can understand people's actions and learn new behaviours in response, even though it is devoid of arms. Robots can be programmed to understand an elderly person's preferences and habits to detect changes in behaviour: for example if a yoga devotee misses a class, it will ask why, while if an elderly person falls it will automatically alert caregivers or emergency services.