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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.

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.

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.

In a series of experiments published in Nature Communications, we found evidence that human judgments are indeed systematically influenced by adversarial perturbations.

The system required a bespoke interface that could accurately test each battery for thermal runaway, and then export and transmit the data to a server to be cross-referenced and analyzed where anomalies were found to be present.

Claire chatted to Rav Chunilal from Sellafield all about robotics and AI for nuclear decommissioning.

Rav Chunilal is the Head of Robotics & Artificial Intelligence at Sellafield Ltd, the UK’s largest nuclear site. He is responsible for developing and deploying Robotics and AI technologies to decommission the site safely, efficiently, and cost-effectively. Under Rav’s leadership, Sellafield Ltd and the Nuclear Decommissioning Authority Group has established itself as a leader in the use of Robotics and AI for nuclear decommissioning. The company has developed and deployed a wide range of robotic technologies to perform tasks such as remote inspection, waste handling, and demolition.