This foundational robotics patent using advanced "swarm robotics" achieves radical reductions of cost and quantum advances in manufacturing techniques for a wide variety of applications—including large scale lighter than air airships.
By the end of this guide, you will have a basic understanding of the components needed to set up a mesh network, strategies to overcome common roadblocks for long-range, ground networks and the steps required to get the network up and running.
Introducing AutoRT, SARA-RT, and RT-Trajectory
Introducing AutoRT, SARA-RT, and RT-Trajectory
Introducing AutoRT, SARA-RT, and RT-Trajectory
Introducing AutoRT, SARA-RT, and RT-Trajectory
Introducing AutoRT, SARA-RT, and RT-Trajectory
Introducing AutoRT, SARA-RT, and RT-Trajectory
Introducing AutoRT, SARA-RT, and RT-Trajectory
Introducing AutoRT, SARA-RT, and RT-Trajectory
For drones to save lives in search and rescue missions, or even reliably deliver our packages, they need to navigate dynamic environments without accident. Unmanned aerial vehicles (UAVs) have had success steering through open spaces time and time again, but the unpredictability of moving obstacles has been a challenge, especially in indoor environments with no GPS signals. Kenji Shimada and his students leaned into this problem to develop new technology that enables autonomous flights in indoor dynamic environments.
Advances in machine learning technology have made once-unreliable vision-guided robots an attainable, commercially viable reality. These systems improve assembly line precision in many ways.
In a series of experiments published in Nature Communications, we found evidence that human judgments are indeed systematically influenced by adversarial perturbations.
In a series of experiments published in Nature Communications, we found evidence that human judgments are indeed systematically influenced by adversarial perturbations.
In a series of experiments published in Nature Communications, we found evidence that human judgments are indeed systematically influenced by adversarial perturbations.