On Friday 22 November, IEEE Robotics and Automation Society will be hosting an online science communication training session for robotics and AI researchers. The tutorial will introduce you to science communication and help you create your own story through hands-on activities. It helps demystify robotics and AI for a broad range of people including policy makers, business leaders, and the public. As a researcher, mastering this skill can not only enhance your communication abilities but also expand your network and increase the visibility and impact of your work. In this three-hour session, leading science communicators in robotics and AI will teach you how to clearly and concisely explain your research to non-specialists.

We're pleased to announce that we will be giving a short introduction to science communication for roboticists at the International Conference on Intelligent Robots and Systems (IROS) this year. This will be held in person and via a livestream on Tuesday 15 October from 13:00 GST (09:00 UTC), and will be run in collaboration with IEEE Spectrum. If you fancy finding out how you can communicate your research to a general audience in different formats, then please do join us. Following an hour-long introductory talk, there will be an optional, open, drop-in session where you can try out some of the things you learnt in the course, ask any sci-comm questions, or chat about your ideas and stories. You can also watch online via a livestream.

Humans don't just lie to deceive: sometimes we lie to avoid hurting others, breaking one social norm to uphold another. As robots begin to transition from tools to team members working alongside humans, scientists need to find out how these norms about deception apply to robots. To investigate this, researchers asked people to give their opinions of three scenarios in which robots were deceptive. They found that a robot lying about the external world to spare someone pain was acceptable, but a robot lying about its own capabilities wasn't -- and that people usually blame third parties like developers for unacceptable deceptions. Honesty is the best policy… most of the time.

There are various desired capabilities to create aerial forest-traversing robots capable of monitoring both biological and abiotic data. The features range from multi-functionality, robustness, and adaptability. These robots have to weather turbulent winds and various obstacles such as forest flora and wildlife thus amplifying the complexity of operating in such uncertain environments. The key for successful data collection is the flexibility to intermittently move from tree-to-tree, in order to perch at vantage locations for elongated time. This effort to perch not only reduces the disturbance caused by multi-rotor systems during data collection, but also allows the system to rest and recharge for longer outdoor missions. Current systems feature the addition of perching modules that increase the aerial robots' weight and reduce the drone's overall endurance. Thus in our work, the key questions currently studied are: "How do we develop a single robot capable of metamorphosing its body for multi-modal flight and dynamic perching?", "How do we detect and land on perchable objects robustly and dynamically?", and "What important spatial-temporal data is important for us to collect?"

Benchmarking, standards and certification are closely related processes. Standards can provide normative requirements that robotics and AI systems may or may not conform to. Certification generally relies upon conformance with one or more standards as the key determinant of granting a certificate to operate. And benchmarks are sets of standardised tests against which robots and AI systems can be measured. Benchmarks therefore can be thought of as informal standards. In this paper we will develop these themes with examples from benchmarking, standards and certification, and argue that these three linked processes are not only useful but vital to the broader practice of Responsible Innovation.

Manuela Veloso won the 2023 Robert S. Engelmore Memorial Award, which recognises outstanding contributions to automated planning, machine learning and robotics, their application to real-world problems and extensive service to the AI community. The winner of this prize is invited to give a lecture at the annual conference on Innovative Applications of Artificial Intelligence (IAAI) (which is collocated with the AAAI Conference on Artificial Intelligence, and this year took place from 7-14 February). Manuela's talk focussed on her research on autonomous robots, and how she has transferred expertise and knowledge from that domain to the field of AI in finance. In both cases, humans interact with AI systems to jointly solve complex end-to-end problems. Manuela began her research career investigating autonomous robots.

The researchers hoped to use their system to improve natural conversations between robots and people. To foster empathy in conversation, scientists at Kyoto University developed a shared-laughter AI system that reacts properly to human laughter. What makes something hilarious has baffled philosophers and scientists since at least the time of inquiring minds like Plato. The Greeks believed that feeling superior at others' expense was the source of humor. Sigmund Freud, a German psychologist, thought humor was a means to let off pent-up energy.

Artificial intelligence and machine learning have been the two hot trending technologies for quite a while now. However, the interest in these new-age technologies peaked significantly right after the onset of coronavirus, when the world was looking forward to digital tools and platforms for sustenance. According to an IDC report, the global revenue of the AI market touched US$ 156.5 billion, marking a jump of 12.3% from 2019. This trend is only bound to rise further up in the next few years. Of all the diverse fields of artificial intelligence, robotics has gained massive popularity across industries, and rightly so.

Professor Chad Jenkins has been elected a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI). Jenkins specializes in mobile manipulation robots and human-robot interaction. His research explores how to enable robots to learn from human demonstration in complex environments. His work has been supported through a number of prestigious awards, including a PECASE award, an NSF CAREER Award, an ONR Young Investigator Award, and a Sloan Research Fellowship. Jenkins is also devoted to ensuring that the fields of robotics and AI are accessible to everyone.

But the transition from tech-focused research group to product-focused startup isn't easy to make; fortunately three experts in the matter joined us at TC Sessions: Robotics to discuss a few ways to get through it successfully. Milo Werner is a new general partner at MIT's The Engine, an accelerator and fund focused on "tough tech." Joyce Sidopoulos is a co-founder of MassRobotics, a community and advocacy group for the sector's startup ecosystem. Our panel started out with some of the most obvious technical considerations founders need to keep in mind when shifting from a research to a mass production process. Werner pointed out that many founders, having come off four to eight years of work in the area, have a passion and familiarity with the material that's difficult to match -- but that can be a barrier to building a team.