Researchers at Stanford have developed a new path planning algorithm that enables autonomous multi-drone aerial surveys over large-scale environments. Their system solves the problem of finding routes over large areas in order to complete aerial survey tasks in reduced time.
Robots will need sensory skins to safely interact with humans and navigate more complex environments than factory work cells. This invention is a new stretchable pneumatic sensor skin that can feel its surroundings and reach for objects in constrained environments.
Multiplexed analysis of biological components is critical for classifying molecular subtypes of heterogeneous tumors to provide patient-specific therapies.
Stanford researchers in the Kanan group have developed a electrolysis cell for generating and extracting liquid and gas product streams from CO and CO2.
Researchers at Stanford have developed a cloud-based behind-the-meter (BTM) system that can cut energy costs and reduce reliance on the grid close to 93% respectively.
Stanford researchers have developed new Fast Quick Error Detection (Fast QED) tests that are four orders of magnitude faster than standard QED tests while also preserving quick error detection properties.
The Foundational QED embodies a set of source code files for performing the basic EDDI, CFCSS, and CFTSS QED transformations for creating tests with extremely short error detection latencies and high error detection coverage.
Stanford researchers have developed new Fast Quick Error Detection (Fast QED) tests that are four orders of magnitude faster than standard QED tests while also preserving quick error detection properties.
During post-silicon validation and debug, manufactured integrated circuits (ICs) are tested in actual system environments to detect and fix design flaws (bugs). Existing techniques are costly due to ad hoc, manual methods.
Stanford engineers have prototyped and tested a flexible, soft growing robot that can deploy sensor networks for investigation in constrained spaces (see video below). Existing sensors for growing robots have focused on moving with the tip of the robot.