Falling cat problem is well-known where cats show their super aerial reorientation capability and can land safely. For their robotic counterparts, a similar falling quadruped robot problem, has not been fully addressed, although achieving safe landing as the cats has been increasingly investigated. Unlike imposing the burden on landing control, we approach to safe landing of falling quadruped robots by effective flight phase control. Different from existing work like swinging legs and attaching reaction wheels or simple tails, we propose to deploy a 3-DoF morphable inertial tail on a medium-size quadruped robot. In the flight phase, the tail with its maximum length can self-right the body orientation in 3D effectively; before touch-down, the tail length can be retracted to about 1/4 of its maximum for impressing the tail's side-effect on landing. To enable aerial reorientation for safe landing in the quadruped robots, we design a control architecture, which has been verified in a high-fidelity physics simulation environment with different initial conditions. Experimental results on a customized flight-phase test platform with comparable inertial properties are provided and show the tail's effectiveness on 3D body reorientation and its fast retractability before touch-down. An initial falling quadruped robot experiment is shown, where the robot Unitree A1 with the 3-DoF tail can land safely subject to non-negligible initial body angles.

Verdict has listed five of the companies that trended the most in Twitter discussions related to disruptive tech, using research from GlobalData's Technology Influencer platform. The top companies are the most mentioned companies among Twitter discussions of more than 513 disruptive tech experts tracked by GlobalData's Technology Influencer platform during the second quarter (Q2) of 2022. OpenAI's text-to-image engine DALL·E 2 not understanding some mysterious language, and the company's release of GPT-3, a new generative language model, were some of the popularly discussed topics in Q2. Spiros Margaris, a venture capitalist and board member at the venture capital firm Margaris Ventures, shared an article on the artificial intelligence (AI) company, OpenAI, having found its text-to-image engine DALL·E 2 to show peculiar behaviours, including something that may be hidden or a fictional language. According to Giannis Daras, a PhD student at the University of Texas at Austin, the AI model produced an artwork when given the input "apoploe vesrreaitais eating Contarra ccetnxniams luryca tanniounons", which makes no sense to humans but the machine generated images of birds eating bugs constantly, the article detailed.

We present a test platform for visual in-cabin scene analysis and occupant monitoring functions. The test platform is based on a driving simulator developed at the DFKI, consisting of a realistic in-cabin mock-up and a wide-angle projection system for a realistic driving experience. The platform has been equipped with a wide-angle 2D/3D camera system monitoring the entire interior of the vehicle mock-up of the simulator. It is also supplemented with a ground truth reference sensor system that allows to track and record the occupant's body movements synchronously with the 2D and 3D video streams of the camera. Thus, the resulting test platform will serve as a basis to validate numerous incabin monitoring functions, which are important for the realization of novel human-vehicle interfaces, advanced driver assistant systems, and automated driving. Among the considered functions are occupant presence detection, size and 3D-pose estimation, and driver intention recognition. In addition, our platform will be the basis for the creation of large-scale in-cabin benchmark datasets.

Toyota Research Institute (TRI) will debut the latest version of its automated driving research vehicle at CES next week. TRI had three major goals with this latest model and Platform 3.0 incorporates them all into a car with more perception capabilities, a design that's easier to produce at scale and a much sleeker look. "To elevate our test platform to a new level, we tapped Toyota's design and engineering expertise to create an all-new test platform that has the potential to be a benchmark in function and style," TRI CEO Gill Pratt said in a statement. First, the vehicle now has 360-degree LiDAR sensing -- previous platforms only had forward-facing LiDAR sensing capabilities -- and new shorter-range LiDAR sensors placed lower to the ground allow for detection of smaller objects like road debris or children. Secondly, Platform 3.0, built on a Lexus LS 600hL, will go into low-volume production this spring and will come in two versions. One will feature a dual cockpit design, allowing for TRI to experiment with methods that transfer driving control between humans and the automated system.