BRAIN: A Low-Power Deep Search Engine for Autonomous Robots
By Lori Cameron
Autonomous robots are actively studied for many unmanned applications. However, the heavy costs and limited battery life make it difficult to implement intelligent decision-making in robots.
In response, researchers propose a low-power deep search engine (code-named “BRAIN”) for real-time path planning of intelligent autonomous robots. To achieve low power consumption while maintaining high performance, BRAIN adopts a multi-threaded core architecture with a transposition table cache to detect and avoid duplicated searches between the processors at the deeper level of the search tree.
BRAIN achieves fast search speed and low energy consumption, while the robots navigate successfully without collision. Read more about this innovative search engine (login may be required for full text) in the September/October 2017 issue of IEEE Micro.
About Lori Cameron
Lori Cameron is a Senior Writer for the IEEE Computer Society and currently writes regular features for Computer magazine, Computing Edge, and the Computing Now and Magazine Roundup websites. Contact her at l.cameron@computer.org. Follow her on LinkedIn.
