Researchers at the University of California, Davis have developed a framework that enables autonomous systems to plan paths while accounting for how their actions influence surrounding actors. Unlike existing approaches that rely on reactive planning with fixed predictions or on computationally intensive multi-agent formulations, this technology uses a structured, data-driven interaction model within a tractable theoretical framework. The approach is designed for real-time deployment and supports analyzable performance and safety behavior under defined conditions. It enables more adaptive navigation in environments shared with people or other intelligent machines, improving operational efficiency, safety margins, and integration potential across a range of autonomous products.

Researchers at the University of California, Davis have developed a system and method to continuously separate granular material mixtures based on differences in their frictional properties using non-antiperiodic vibratory excitation.

Researchers at the University of California, Davis have developed a system of reusable, sterilizable 3D-printed surgical tools that enables safe, precise intraoperative deployment of Neuropixels probes within standard neurosurgical workflows.

Researchers at the University of California, Davis have developed tactile feedback systems that enhance spatial and sensory resolution in sensor arrays through unique signal modulation techniques.

Researchers at the University of California, Davis have developed an approach to enhance autonomous vehicle path prediction through efficient information sharing and distributed learning among AI agents.

Researchers at the University of California, Davis have developed a technology that introduces a highly adaptable, lightweight robotic end effector designed for complex manipulation tasks in automation.

Researchers at the University of California Davis have developed a system designed to predict and prevent ATV rollovers, enhancing rider safety.

Researchers at the University of California Davis have developed a technology that enables the provable editing of DNNs (deep neural networks) to meet specified safety criteria without altering their architecture.

Researchers at the University of California, Davis have developed an algorithm for designing and identifying complex structures having custom release profiles for controlled drug delivery.

Researchers at the University of California, Davis have developed a haptic interface designed to aid visually impaired individuals in navigating their environment using their portable electronic devices.

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.

Researchers at the University of California, Davis have developed an autonomous crop transportation robot to aid field workers during harvest.

Researchers at the University of California, Davis have developed a system consisting of cameras and multi-wavelength lasers that is capable of precisely locating and inspecting items.

Researchers at the University of California, Davis have developed a programmable machine that shakes and repeatedly inverts large numbers of small containers - such as vials and flasks – in order to mix high-viscosity fluids.

Researchers at the University of California, Davis have developed a robotic dispensing interface that uses a microfluidic-embedded container cap – often referred to as a microfluidic Cap-to-Dispense or μCD - to seamlessly integrate robotic operations into precision liquids handling.

Researchers at the University of California, Davis have developed a controller that applies environmental data to optimizing operations of livestock cooling equipment.