The climate emergency brooks no compromise: every human activity or artefact is either part of the solution or it is part of the problem. I've worried about the sustainability of consumer electronics for some time, and, more recently, the shocking energy costs of big AI. But the climate emergency has also caused me to think hard about the sustainability of robots. And, I'm ashamed to say, very little robotics research is focused on the development of sustainable robots. A search on google scholar throws up a handful of excellent papers detailing work on upcycled and sustainable robots (2018), sustainable robotics for smart cities (2018), green marketing of sustainable robots (2019), and sustainable soft robots (2020).
In this technical talk, Amanda Prorok, Assistant Professor in the Department of Computer Science and Technology at Cambridge University, and a Fellow of Pembroke College, discusses her team's latest research on what, how and when information needs to be shared among agents that aim to solve cooperative tasks. Effective communication is key to successful multi-agent coordination. Yet it is far from obvious what, how and when information needs to be shared among agents that aim to solve cooperative tasks. In this talk, I discuss our recent work on using Graph Neural Networks (GNNs) to solve multi-agent coordination problems. In my first case-study, I show how we use GNNs to find a decentralized solution to the multi-agent path finding problem, which is known to be NP-hard.
Since 2007, two professors at the TU Delft have been researching ways to harvest energy from the wind using a kite. The robotic kite looks set to make its debut in the energy sector, but often inventions are used in unexpected ways. In this series of articles, we take robot innovations from their test-lab and bring them to a randomly selected workplace in the outside world. From kindergarten teacher Fransien, we learn that big kites could also be child's play, quite literally. A robot wheels in the kite and then slowly releases it, painting 8-shaped loops on the sky.
In 2018, five patients at the Apex Heart Institute in Ahmedabad, India, received treatment for coronary artery disease (CAD) the same way 3 million others do each year: a small balloon was inserted into an artery in the heart and inflated, making way for the placement of a stent to keep the vital pathway open. The procedure, known as percutaneous coronary intervention (PCI), is the standard treatment for atherosclerosis, a common CAD marked by the buildup of plaque inside the arteries and a subsequent restriction of blood flow. Like many patients before them, their operation was assisted by a robot--the CorPath GRX robotic platform from Corindus, A Siemens Healthineers Company. Yet unlike anyone else before them, these five patients were part of an amazing first: their principal physician was not in the room with them during the procedure. In fact, he was 20 miles away, guiding the robot--performing the operation to perfection--from a remote workstation.
Talking Robotics is a series of virtual seminars about Robotics and its interaction with other relevant fields, such as Artificial Intelligence, Machine Learning, Design Research, Human-Robot Interaction, among others. They aim to promote reflections, dialogues, and a place to network. In this seminars compilation, we bring you 7 talks (and a half?) from current roboticists for your enjoyment. Filipa Correia received a M.Sc. in Computer Science from University of Lisbon, Portugal, 2015. She is currently a junior researcher at GAIPSLab and she is pursuing a Ph.D. on Human-Robot Interaction at University of Lisbon, Portugal.
The updates coincide with the annual National Robotics Week, a time when kids, parents and teachers across the nation tap into the excitement of robotics for STEM learning. Supporting Social and Emotional Learning The events of the past year changed the traditional learning environment with students, families and educators adapting to hybrid and remote classrooms. Conversations on the critical importance of diversity, equity and inclusion have also taken on increased importance in the classroom. To address this, iRobot Education has introduced social and emotional learning (SEL) lessons to its Learning Library that tie SEL competencies, like peer interaction and responsible decision-making, into coding and STEM curriculum. These SEL learning lessons, such as The Kind Playground, Seeing the Whole Picture and Navigating Conversations, provide educators with new resources that help students build emotional intelligence and become responsible global citizens, through a STEM lens. Language translations for iRobot Coding App More students can now enjoy the free iRobot Coding App with the introduction of Spanish, French, German, Czech and Japanese language support.
This episode is about understanding why you can't build your startup alone, and some criteria to properly select your co-founders. In this podcast series of episodes we are going to explain how to create a robotics startup step by step. We are going to learn how to select your co-founders, your team, how to look for investors, how to test your ideas, how to get customers, how to reach your market, how to build your product… Starting from zero, how to build a successful robotics startup. I'm Ricardo Tellez, CEO and co-founder of The Construct startup, a robotics startup at which we deliver the best learning experience to become a ROS Developer, that is, to learn how to program robots with ROS. Our company is already 5 years long, we are a team of 10 people working around the world.
In recent years, robots have gained artificial vision, touch, and even smell. "Researchers have been giving robots human-like perception," says MIT Associate Professor Fadel Adib. In a new paper, Adib's team is pushing the technology a step further. "We're trying to give robots superhuman perception," he says. The researchers have developed a robot that uses radio waves, which can pass through walls, to sense occluded objects.
Mapping is an essential task in many robotics applications. A map is a representation of the environment generated from robots positions and sensors data. A map can be either used to navigate the robot that built it, or shared with other agents: humans, software, or robots. To build a map, it is frequently assumed that the positions of the robots are a priori unknown and need to be estimated during operation. Accordingly, the problem that robots must solve is known as simultaneous localization and mapping (SLAM). This problem has been extensively studied in the past decades.
Amanda Prorok is an Assistant Professor (University Lecturer) in the Department of Computer Science and Technology, at Cambridge University, and a Fellow of Pembroke College. She serves as Associate Editor for IEEE Robotics and Automation Letters (R-AL) and Associate Editor for Autonomous Robots (AURO). Prior to joining Cambridge, Prorok was a postdoctoral researcher at the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory at the University of Pennsylvania, USA, where she worked with Prof. Vijay Kumar. She completed her PhD at EPFL, Switzerland, with Prof. Alcherio Martinoli.