Recent Robotics and Autonomous Systems Articles - Elsevier.
The aim of the CCNR is to encourage a two-way flow of ideas and methods between the Life and Computational sciences and the benefits of a cross-disciplinary approach are reflected in the nature of the research that is carried out here. Some of the research in the Centre can be characterised as Biologically-Inspired Engineering, this includes autonomous agent research and evolutionary robotics.
This Research Topic is devoted to publishing extended versions of the Best Papers presented at the first international conference on Soft Robotics (RoboSoft) held on 24-28 April 2018 in Livorno, Italy.The field of soft robotics has grown significantly in the last decade and has delivered remarkable achievements in terms of new principles, design approaches, technologies, and fabrication.
The course will largely cover relevant papers published within the last few years in computer vision, robotics, and machine learning. Students should be familiar with reading and critiquing research papers, and should have a basic understanding of concepts in artificial intelligence, and machine learning. Students must have taken at least one of the following (or equivalent) courses: ECE 448.
The Supernumerary Robotic Limbs (SRL) prototype. A) The structure of the SRL: the robot is worn at the hip of the user, and its limbs can act both as arms and as legs. Each robotic limb has 3dof: two rotational ones at its base, and one linear one in the limb itself. B) and C) Lateral and posterior view of the SRL prototype. Research The research on the Supernumerary Robotic Limbs started from.
MIT designs robot to be a good pedestrian and not bump into you on the sidewalk Engineers at MIT are working on instilling robots with “socially aware” navigation, allowing them to observe humans’ code of pedestrian conduct. Generally speaking, mo.
Welcome to the Resilient Intelligent Systems Lab (RISLab), part of the Field Robotics Center at the Robotics Institute, Carnegie Mellon University. Our goal is to improve the performance and reliability of autonomous systems that must operate in challenging, real-world scenarios.
Research We work on some of the most complex and interesting challenges in AI. Our world-class research has resulted in hundreds of peer-reviewed papers, including in Nature and Science.