Abstract: A follow-hold switch circuit comprising: a follower; a sampling sub-circuit for voltage sampling; a bootstrap-control sub-circuit, which provides a bootstrap voltage to the sampling sub-circuit when the circuit is in a following state; a sampling-switch-control sub-circuit, which provides a common-mode voltage to a bootstrap capacitor in the bootstrap-control sub-circuit when the circuit is in a holding state; the follower is connected to an output of the sampling sub-circuit; the sampling sub-circuit is connected to the bootstrap-control sub-circuit and the sampling-switch-control sub-circuit respectively through a sampling switch; the present disclosure can effectively improve the linearity of sampling switches.

Abstract: This application relates to the field of artificial intelligence. The technology includes: obtaining data of each three-dimensional point in a first three-dimensional point set, where the data of each three-dimensional point is collected when an intelligent device is in a first position, and the first three-dimensional point set includes a plurality of three-dimensional points located in a first coordinate system; determining a first three-dimensional point subset from the first three-dimensional point set, where the first three-dimensional point subset forms a first plane; calculating a plurality of first distances, which is a distance between a first three-dimensional point and the first position; determining a target first three-dimensional point from the first three-dimensional point subset based on the plurality of first distances; and locating the intelligent device by using the target first three-dimensional point as a constraint to obtain a pose of the first position.

Abstract: One example method includes obtaining a state vector set, where the state vector set includes at least one of a pose vector of an intelligent device or a landmark characteristic vector of an environment in which the intelligent device is located, determining a first linearized constraint equation, determining a first state vector, marginalizing the first state vector in the first linearized constraint equation to obtain a second linearized constraint equation, determining an objective function based on the second linearized constraint equation, and optimizing the at least one of the at least one pose vector or the at least one landmark characteristic vector based on the objective function to output a track of the intelligent device and a map of the environment in which the intelligent device is located.