Researchers at the University of California, Davis have developed an automated harvesting system using predictive scheduling for crop-transport robots, reducing manual labor, and increasing harvesting efficiency.

 The dynamic patterning of 3D optical point clouds has emerged as a key enabling technology in volumetric processing across a number of applications. In the context of biological microscopy, 3D point cloud patterning is employed for non-invasive all-optical interfacing with cell ensembles. In augmented and virtual reality (AR/VR), near-eye display systems can incorporate virtual 3D point cloud-based objects into real-world scenes, and in the realm of material processing, point cloud patterning can be mobilized for 3D nanofabrication via multiphoton or ultraviolet lithography. Volumetric point cloud patterning with spatial light modulators (SLMs) is therefore widely employed across these and other fields. However, existing hologram computation methods, such as iterative, look-up table-based and deep learning approaches, remain exceedingly slow and/or burdensome. Many require hardware-intensive resources and sacrifices to volume quality.To address this problem, UC Berkeley researchers have developed a new, non-iterative point cloud holography algorithm that employs fast deterministic calculations. Compared against existing iterative approaches, the algorithm’s relative speed advantage increases with SLM format, reaching >100,000´ for formats as low as 512x512, and optimally mobilizes time multiplexing to increase targeting throughput. 

Brief description not available

Brief description not available

The field of autonomous transportation is rapidly evolving to operate in diverse settings and conditions. However, as the number of autonomous vehicles on the road increases the complexity of the computations needed to safely operate all of the autonomous vehicles grows rapidly. across multiple vehicles, this creates a very large volume of computations that must be performed very quickly (e.g., in real or near-real time).   Thus, treating each autonomous vehicle as an independent entity may result in inefficient use of computing resources, as many redundant data collections and computations may be performed (e.g., two vehicles in close proximity may be performing computations related to the same detected object). To address this issue, researches at UC Berkeley proposed algorithms for the management and exchange of shared information across nearby and distant vehicles.According to the proposed arrangement, autonomous vehicles may share data collected by their respective sensor systems with other autonomous vehicles and adjust their operations accordingly in a manner that is more computationally efficient. This can not only increase safety but at the same time reduce computational load required by each individual vehicle.

The field of autonomous transportation is rapidly evolving to operate in diverse settings and conditions.  Critical to the performance of autonomous vehicles is the ability to detect other objects in the autonomous vehicle’s vicinity and adjust accordingly. To do so, many autonomous vehicles utilize a variety of sensors, including sonar. Although these sensor systems have been shown to improve the safety of autonomous vehicles by reducing collisions, the sensor systems tend to be computationally inefficient.  For instance, the sensor systems may generate large volumes of data that must be processed quickly (e.g., in real or near-real time).  The performance of excessive computations may delay the identification and deployment of necessary resources and actions and/or increase the cost of hardware on the vehicle making it less financially appealing to the consumer. Researches at UC Berkeley proposed algorithms for temporally and spectrally adaptive sonar systems for autonomous vehicles. These allow utilization of existing sonar system in an adaptive manner and in interface with existence hardware/software employed on autonomous vehicles. 

Researchers at the University of California, Davis have developed an amplifier technology that boosts power output in order to improve data transmission speeds for high-frequency communications.

Need to transport sturdy adjustable workbenches for use at sea or other temporary work spaces that need anchoring to walls or floors and you can't find a commercially available source?

Brief description not available

The number one cause of train derailments globally are unidentified track defects which accumulate over time under the heavy loads and weathering to which rail is exposed. For the last 100 years rail inspection has sought to identify these structural defects before they can pose a serious threat to regular rail traffic. Unfortunately, rail inspection has required specialized low-speed testing cars which can only operate at less than 25% the normal speed of a train. These inspection cars must coordinate their work around planned outages of the rail line, impacting normal rail traffic. Due to this inconvenience, rail defects are typically repaired in real-time, as identified, vs. being prioritized as to potential seriousness and repaired in order of likelihood to cause a future accident.

While cellular phone networks are not designed for navigation, they are abundant in urban environments which are known to challenge GPS signals.  University of California, Riverside researchers integrated signals-of-opportunity from mobile phone networks to provide autonomous vehicles with precise navigational information.

Nanocrystalline iron nitride is an important soft magnetic material; however, conventional methods of production don’t exist. Synthesis of dense nanocrystalline iron nitrides is not possible by simply annealing elemental iron in NH3 at temperatures in excess of 600° C since g’-Fe4N and other iron nitrides are unstable above 600°C and will decompose. Sandia researchers have discovered that by using a two-step reactive milling process and high pressure spark plasma sintering (SPS) they can quickly and efficiently fabricate bulk g’-Fe4N parts.

This technology combines air layer frictional drag reduction (ALDR) with super hydrophobic surfaces (SHS) to achieve frictional drag reduction of ALDR with significantly reduced gas flux. Thus, enabling increased net energy savings. The stable air layer is achieved with lesser gas flux when utilizing a SHS.Periodic air layers may replenish SHS, enabling drag reduction with reduced energy cost. Combinations of SHS and regular or other non-SHS surface may be used to control spreading of gas, thus facilitating formation of ALDR using discrete gas injection points better than previously achievable. Such surface variations could also be used to preferentially guide gas towards or away from propulsion, depending on desired outcome. By controlling ALDR regionally or globally on a surface, with or without SHS, this technology modifies flow around a hull. This mediates forces on partially or fully submerged objects, enabling control of flow patterns, resistance, steering, and/or dynamics.

Researchers at the University of California, Davis have developed a new flight mechanism that offers vertical take-off and landing (VTOL) capability and cruising speeds comparable with fixed wing unmanned aerial vehicles (UAV).

As improvements in technology allow for construction of bigger, more uniquely designed skyscrapers, bridges, and motorways that can carry greater loads and are seismically sound, current cement composites are being pushed to their performance limits. Now more than ever, assessing damage to cement composite structures is of integral importance. However, traditional methods can be destructive, subjective, and may not detect previously existing damage, which can be invisible to the naked eye or hidden beneath structural surfaces. Addition of conductive additives, such as carbon nanotubes (CNTs) to cementitious composites attributes both load-bearing and damage self-sensing properties to the composites. However, current formulations and methods for producing these multifunctional cement composites require specialized equipment, are labor, time, and capital intensive, and are not scalable.

The invention relates to the field of micromachined gyroscopes, and in particular to inertial micromachined transducers for measurement of angular rotation rate of an object. A three-degrees of freedom (DOF) MEMS inertial micromachined gyroscope with nonresonant actuation with a drive direction, sense direction and a direction perpendicular to the drive and sense directions comprises a planar substrate, a 2-DOF sense-mode oscillator coupled to the substrate operated at a flattened wide-bandwidth frequency region, and a 1-DOF drive mode oscillator coupled operated at resonance in the flattened wide-bandwidth frequency region to achieve large drive-mode amplitudes.

Researchers at the University of California, Davis have developed an innovative synthesis approach to achieve high anisotropy L1 FeNi by combining physical vapor deposition and a high speed rapid thermal annealing (RTA).

Researchers at the University of California, Davis have developed a novel mechanism for vectoring the thrust of supersonic, air-breathing jet engines for aircraft applications.

Researchers at the University of California, Davis have developed a tri-energy source (TES) hybrid vehicle powertrain consisting of three different propulsion systems including: (i) an internal combustion engine (ICE); (ii) an electric motor and battery and; (iii) a flywheel and continuously variable transmission (CVT).

UCLA researchers have developed an accurate low-profile shear sensing unit that is viable for both gas and liquid flows.

Brief description not available

Background: Current navigation systems offer “shortest-distance” or “shortest-time” functions to help avoid traffic congestion but neither of them determine the most fuel efficient route. With rising gas prices and vehicle emissions, a more advanced navigation system with additional functions, such as an environmentally-friendly feature, is needed. This accomplishment can make a huge improvement on increasing fuel costs and air pollution. The in-vehicle navigation system is also expected to competitively penetrate the US market in the next couple years with annual sales quadrupling to $13M.  Brief Description: UCR researchers have developed an innovative vehicle navigation system (VNS) that will allow users to choose a route that is the most gas efficient and emanates less emissions. The energy- and emissions-minimization function is incorporated on top of distance- and time-minimizing functions that currently exists in the traditional VNS. This new intelligent transportation system utilizes a state-of-the-art modal emissions model (CMEM) that encompasses real-world vehicle activity patterns, and can calculate the fuel consumption and emission values of each vehicle trajectory.

Trillions of sensors are envisioned to achieve the potential benefits of the internet of things.  Realizing this potential requires wireless sensors with low power requirements such that there might never be a need to replace a sensor’s power supply (e.g. battery) over the lifetime of that device.  The battery lifetime of wireless communications devices is often governed by power consumption used for transmitting, and therefore transmit power amplifiers used in these devises are important to their commercial success.  The efficiencies of these power amplifiers are set by the capabilities of the semiconductor transistor devices that drive them.  To achieve improved efficiencies, researchers at UC Berkeley have developed a novel method and structure for realizing a zero-quiescent power trigger sensor and transceiver based on a micromechanical resonant switch.  This sensor/transceiver is unique in its use of a resonant switch (“resoswitch”) to receive an input, amplify it, and finally deliver power to a load.  This novel technology also greatly improves short-range communication applications, like Bluetooth.  For example, with this technology, interference between Bluetooth devices would be eliminated.  Also, Miracast would work, despite the presence of interfering Bluetooth signals.

This invention consists of a rapid, simplified, lower-cost method for production of a cement composite with enhanced load-bearing and damage detecting properties.

There are many applications that require the storage of a high density of gas molecules. The driving range of vehicles powered by natural gas or hydrogen, for instance, is determined by the maximum density of gas that can be stored inside a fuel tank and delivered to the engine or fuel cell. In certain situations, it is desirable to lower the pressure or raise the temperature needed to store a given amount of gas through the use of an adsorbent. Developments in next-generation adsorbents, such as metal-organic frameworks and activated carbons, have shown certain weaknesses in terms of the amount of gas that can be delivered when an application has a minimum desorption pressure greater than zero and when a significant amount of heat is released during adsorption or cooling occurs during desorption. To help solve these problems, researchers at the University of California, Berkeley, have developed a next generation of materials using novel porous metal-organic frameworks that demonstrate unprecedented deliverable gas capacities. These engineered adsorbents maximize the amount of gas delivered during each adsorption/desorption cycle. This shows promise in developing next generation gas storage materials for applications with a wide range of operating conditions.