Federal funding develops the basis for autonomous robots
in: Prosperity
For modern robots, like self-driving cars, successfully navigating our complex world is a fundamental requirement. It’s not enough for them just to follow a pre-programmed path. They need to perform two critical tasks simultaneously: figuring out their precise location (“Where am I?”) while also building and updating a detailed map of their immediate environment (“What’s around me?”). This challenging process is called Simultaneous Localization And Mapping, or SLAM.
Key developments enabling SLAM technology originated from research supported by agencies like NASA, initially envisioned for robots exploring unknown terrains autonomously. Today, SLAM forms the foundational software enabling many robots to continuously learn about their surroundings, accurately track their own position within that space, and intelligently plan paths towards their goals. Crucially, this allows them to safely maneuver around both stationary objects and unexpected obstacles that might suddenly appear, a capability essential for the early self-driving cars that won competitions like the DARPA Grand Challenge.
- States: CA
- Organizations: National Aeronautics and Space Administration , United States Air Force
- Topics: Technology , Computer Science
- Federal Grants: NSF ECS-8200615 , Air Force F49620-84-K-0007
- Links and further reading: [ link1 | link2 | link3 | link4 ]