Rajagiri Round Table: Educating India- Listening to Innovative Teachers-76th Rajagiri Round Table  |  Cover Story: A New Era of Instructional Design  |  Best Practices: Continental Hospitals Set up a Super Specialty Clinic in IIT Hyderabad  |  Science Innovations: New cancer treatment developed by MIT  |  Leadership Instincts: Disappearance of Women researchers in Authorship during Pandemic  |  Technology Inceptions: MIT developed a New Successor for Mini Cheetah Robot  |  Science Innovations: IISc team develops novel computational model to predict ‘change blindness’  |  Science Innovations: Immune System Responds Better to Vaccination in Morning Hours  |  Teacher Insights: Training in Childhood Education, New Pedagogy Enabled Innovation in Teaching  |  International Policy: UNESCO Prize for Girls’ and Women’s Education 2021  |  Leadership Instincts: UNESCO Prize for Girls’ and Women’s Education 2021  |  Health Monitor: Intensive therapy better for Cerebral Palsy  |  Parent Interventions: Intensive therapy better for Cerebral Palsy  |  Science Innovations: Intensive therapy better for Cerebral Palsy  |  International Edu News: TutorComp- a new platform for online tutoring in UAE.  |  
July 07, 2021 Wednesday 01:38:12 PM IST

Autonomous Vehicles Recognise Terrains

Science Innovations

A new algorithm has been developed by the California Institute of Technology (Caltech) that allows autonomous vehicle systems to recognise where they are simply by looking at the terrain around them. This new algorithm works regardless of seasonal changes to the terrain. The present visual terrain-relative navigation (VTRN) system depends on close matches to the images in its database to identify terrains. Anything that alters or obscured the terrain, such as snow cover or fallen leaves, causes the images do not to match up and fouls up the system. With the use of deep learning and artificial intelligence (AI), Caltech scientists have been able to remove seasonal content that hinders current VTRN systems. It uses a self-supervised learning technique and the AI looks for patterns in images by teasing out details and features that would likely be missed by humans.