Abstract: A system for monitoring soil moisture within a field during the performance of an agricultural operation with an agricultural implement includes a first soil moisture sensor spaced apart from the field, a second soil moisture sensor supported on the agricultural implement and being of a different sensor type from the first soil moisture sensor, and a computing system that selects a first predetermined relationship associated with an expected soil type at a first location and determines a first moisture content at the first location based on data from the first soil moisture sensor and the first predetermined relationship. Moreover, the computing system determines a second moisture content at the first location based on data from the second soil moisture sensor. Additionally, the computing system determines whether the first predetermined relationship is associated with an actual soil type at the first location based on the first and second moisture contents.

Abstract: A system and methods for operating a multi-robot system (MRS) are disclosed. In some aspects, each robot of the MRS can: determine a local system regret state belief based on local evidence obtained by the robot itself and social evidence provided by other robots in a social community, determine a local system drift state belief based on the local system regret state belief, determine a next action based on the local system regret state belief and the local system drift state belief, and execute the next action. Local system regret state belief is generally an estimation of a system regret state for the MRS. Local system drift state belief is generally an estimate of a system drift state for the MRS.

Abstract: A method for controlling a robot to perform a task. The method includes acquiring, for each target of a sequence of targets comprising at least one intermediate target of the task and a final target of a task, a target image data element comprising at least one target image from a perspective of an end-effector of the robot at a respective target position of the robot and successively according to the sequence of targets, for each target in the sequence, acquiring, for the target, an origin image data element, supplying the origin image data element and the target image data to a machine learning model configured to derive a delta movement between the origin current position and the target position and controlling the robot to move according to the delta movement.