Chipmakers like Nvidia and Qualcomm have been busy building products to bring vision intelligence to robots, but in some scenarios, robots may be better off relying on other capabilities to navigate their surroundings. That's why the latest version of MIT's Cheetah robot, the Cheetah 3, is designed to move across rough terrain and through obstacles without relying on vision. "Vision can be noisy, slightly inaccurate, and sometimes not available, and if you rely too much on vision, your robot has to be very accurate in position and eventually will be slow," the robot's designer, MIT Associate Prof. Sangbae Kim, said in a release. "So we want the robot to rely more on tactile information. That way, it can handle unexpected obstacles while moving fast."
For Muslims in the United States, there is no other time more centered around gathering in congregation than the holy month of Ramadan. In every corner of the country, believers attend community iftar meals to break the fast and then pack neatly into tight rows for nightly prayers at the mosque. On weekends, especially, some may linger longer as they catch up, share in the pre-dawn suhoor meal and line up again for the fajr, dawn, prayers.
The objective of the first CARLA autonomous driving challenge was to deploy autonomous driving systems to lead with complex traffic scenarios where all participants faced the same challenging traffic situations. According to the organizers, this competition emerges as a way to democratize and to accelerate the research and development of autonomous vehicles around the world using the CARLA simulator contributing to the development of the autonomous vehicle area. Therefore, this paper presents the architecture design for the navigation of an autonomous vehicle in a simulated urban environment that attempts to commit the least number of traffic infractions, which used as the baseline the original architecture of the platform for autonomous navigation CaRINA 2. Our agent traveled in simulated scenarios for several hours, demonstrating his capabilities, winning three out of the four tracks of the challenge, and being ranked second in the remaining track. Our architecture was made towards meeting the requirements of CARLA Autonomous Driving Challenge and has components for obstacle detection using 3D point clouds, traffic signs detection and classification which employs Convolutional Neural Networks (CNN) and depth information, risk assessment with collision detection using short-term motion prediction, decision-making with Markov Decision Process (MDP), and control using Model Predictive Control (MPC).
There are no public statistics available for how many Saudi women try to flee abroad each year. The most recent statistics from the Ministry of Labor and Social Development show that 577 Saudi women tried to flee their homes within Saudi Arabia in 2015. That figure is likely to be much higher in reality because many families do not report runaways for fear of social stigma.
Unity Technologies has a new game that you can't play. The maker of game development tools is releasing a new title called Obstacle Tower that is designed to challenge the capabilities of artificial intelligence. The release of the title is being accompanied by a contest, the Obstacle Tower Challenge, that will allow participants to run their AI agents through the 100-level challenge and compete for prizes. According to Unity, Obstacle Tower provides a game-like environment for machine learning researchers to play around with and fine-tune their AI. The tower operates similarly to a standard platforming game.