A foot force acquisition apparatus includes a first connecting rod, a pressure signal acquisition board, a second connecting rod rotatably connected with the first connecting rod, and an air tube provided in the first connecting rod and the second connecting rod. An end portion of the second connecting rod is fixedly provided with an elastic foot pad. An air chamber is provided in the elastic foot pad. One end of the air tube is connected with the air chamber. The other end is connected with the pressure signal acquisition board. By providing the pressure signal acquisition board and providing the air chamber in the foot, the air tube spans a joint formed by the first connecting rod and the second connecting rod to acquire the internal pressure value of the air chamber, thus achieving the advantages of simple structure, low cost and high reliability.

A system for providing 3D surveying of an environment by an autonomous robotic vehicle comprising a SLAM unit for carrying out a simultaneous localization and mapping process, a path planning unit to determine a path to be taken by the autonomous robotic vehicle, and a lidar device. The lidar device is configured to generate the lidar data which allows the SLAM unit to receive the lidar data as part of the perception data for the SLAM process. The path planning unit is configured to determine the path to be taken by carrying out an evaluation of a further trajectory within a map of the environment in relation to an estimated point distribution map for an estimated 3D point cloud, which is provided by the lidar device on the further trajectory and projected onto the map of the environment.

A system for providing 3D surveying of an environment by an autonomous robotic vehicle comprising a SLAM unit for carrying out a simultaneous localization and mapping process, a path planning unit to determine a path to be taken by the autonomous robotic vehicle, and a lidar device. The lidar device is configured to generate the lidar data which allows the SLAM unit to receive the lidar data as part of the perception data for the SLAM process. The path planning unit is configured to determine the path to be taken by carrying out an evaluation of a further trajectory within a map of the environment in relation to an estimated point distribution map for an estimated 3D point cloud, which is provided by the lidar device on the further trajectory and projected onto the map of the environment.

A method for controlling gait of a biped robot includes: collecting a lateral center of mass (CoM) speed and a lateral CoM position of the biped robot when the biped robot walks in place, calculating phase variables of virtual constraints corresponding to the CoM of the biped robot in a first phase and a second phase according to the lateral CoM speed and the lateral CoM position; constructing motion trajectory calculation equations for the biped robot based on the phase variables corresponding to the first phase and the second phase, respectively; and finding inverse solutions for joints of the biped robot using the motion trajectory calculation equations to obtain joint angles corresponding to each of the joints of the biped robot to realize gait control.

A method for controlling gait of a biped robot includes: collecting a lateral center of mass (CoM) speed and a lateral CoM position of the biped robot when the biped robot walks in place, calculating phase variables of virtual constraints corresponding to the CoM of the biped robot in a first phase and a second phase according to the lateral CoM speed and the lateral CoM position; constructing motion trajectory calculation equations for the biped robot based on the phase variables corresponding to the first phase and the second phase, respectively; and finding inverse solutions for joints of the biped robot using the motion trajectory calculation equations to obtain joint angles corresponding to each of the joints of the biped robot to realize gait control.

A robot detects, through a sensor, the location and movement direction of a user and an object near the user, sets a nearby ground area in front at the feet of the user according to the detected location and movement direction of the user, controls an illumination device in the robot to irradiate the nearby ground area with light while driving at least one pair of legs or wheels of the robot to cause the robot to accompany the user, specifies the type and the location of the detected object, and if the object is a dangerous object and is located ahead of the user, controls the illumination device to irradiate a danger area including at least a portion of the dangerous object with light in addition to irradiating the nearby ground area with light.

This disclosure is related to a robot motion control method and apparatus. The method includes: obtaining a center-of-mass reference trajectory used for guiding the robot to execute a target motion; obtaining, based on optimization of an objective function, center-of-mass control information for controlling the robot to follow the center-of-mass reference trajectory to move; generating joint control information according to the center-of-mass control information and a structure matrix of the robot; and controlling the robot to execute the target motion based on the joint control information.

A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to receive sensor data associated with a door. The data processing hardware determines, using the sensor data, door properties of the door. The door properties can include a door width, a grasp search ray, a grasp type, a swing direction, or a door handedness. The data processing hardware generates a door movement operation based on the door properties. The data processing hardware can execute the door movement operation to move the door. The door movement operation can include pushing the door, pulling the door, hooking a frame of the door, or blocking the door. The data processing hardware can utilize the door movement operation to enable a robot to traverse a door without human intervention.

A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to receive sensor data associated with a door. The data processing hardware determines, using the sensor data, door properties of the door. The door properties can include a door width, a grasp search ray, a grasp type, a swing direction, or a door handedness. The data processing hardware generates a door movement operation based on the door properties. The data processing hardware can execute the door movement operation to move the door. The door movement operation can include pushing the door, pulling the door, hooking a frame of the door, or blocking the door. The data processing hardware can utilize the door movement operation to enable a robot to traverse a door without human intervention.

Disclosed are a method and an apparatus for controlling a multi-legged robot, and a storage medium. The method includes: acquiring current state parameters of the multi-legged robot; when types and/or quantities of the current state parameters meet a first preset condition, acquiring a first motion control policy by inputting the current state parameters into a first model generated by training; and controlling the multi-legged robot based on the first motion control policy.