Abstract: A suspension system configured to exhibit low variance in vehicle ride frequency over a large range of vehicle loads. The suspension system includes a strut having a cylinder and a piston configured to reciprocate in the cylinder. The suspension system also includes a vessel coupled to the strut, and a valve in an interior chamber of the vessel. The valve divides the interior chamber into a first liquid volume and a second liquid volume. The suspension system also includes a hydraulic accumulator having a volume and a liquid volume. The suspension system further includes a compressible liquid in the cylinder, the first liquid volume in the vessel, and the second liquid volume in the vessel, and a spring element in the volume of the hydraulic accumulator.

Abstract: Systems and methods are disclosed that relate to freespace detection using machine learning models. First data that may include object labels may be obtained from a first sensor and freespace may be identified using the first data and the object labels. The first data may be annotated to include freespace labels that correspond to freespace within an operational environment. Freespace annotated data may be generated by combining the one or more freespace labels with second data obtained from a second sensor, with the freespace annotated data corresponding to a viewable area in the operational environment. The viewable area may be determined by tracing one or more rays from the second sensor within the field of view of the second sensor relative to the first data. The freespace annotated data may be input into a machine learning model to train the machine learning model to detect freespace using the second data.