Control for controlling a robot that allows selection from among multiple gaits is provided. The control apparatus includes a cost map creation unit that creates a cost map for each of gaits of the robot that allows selection from among multiple gaits, and a path creation unit that creates a path including gait switching for the robot by using the cost maps created by the cost map creation unit. The path creation unit searches for the shortest path by using the cost map of the gait that is high in traversing performance among the multiple gaits, performs search for a gait switching point on the path found out, and researches, in a case where there is a gait switching point, for a path on the cost map of the gait selected by an objective function, by using the gait switching point as a sub goal.

Each of three floors is adjacent to the other two floor robots so that a position at which three vertices selected each from the three floor robots face each other is set as a central point, and an information processing apparatus includes a floor robot guidance unit to specify an advancing direction and a walking speed of a walking person based on pressures detected by the floor robots when the walking person walks, to move the three floor robots at the specified walking speed in an opposite direction to the specified advancing direction, to specify, as a target vertex, a vertex that can be determined to lie in the specified advancing direction, other than the three vertices, and rotate at least one of the three floor robots so that the position of the target vertex is set as a new central point.

Methods, systems, and apparatus, including computer-readable storage devices, for robot navigation using 2D and 3D path planning. In the disclosed method, a robot accesses map data indicating two-dimensional layout of objects in a space and evaluates candidate paths for the robot to traverse. In response to determining that the candidate paths do not include a collision-free path across the space for a two-dimensional profile of the robot, the robot evaluates a three-dimensional shape of the robot with respect to a three-dimensional shape of an object in the space. Based on the evaluation of the three-dimensional shapes, the robot determines a collision-free path to traverse through the space.

A method of planning a swing trajectory for a leg of a robot includes receiving an initial position of a leg of the robot, an initial velocity of the leg, a touchdown location, and a touchdown target time. The method also includes determining a difference between the initial position and the touchdown location and separating the difference between the initial position and the touchdown location into a horizontal motion component and a vertical motion component. The method also includes selecting a horizontal motion policy and a vertical motion policy to satisfy the motion components. Each policy produces a respective trajectory as a function of the initial position, the initial velocity, the touchdown location, and the touchdown target time. The method also includes executing the selected policies to swing the leg of the robot from the initial position to the touchdown location at the touchdown target time.

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.

A method for perception and fitting for a stair tracker includes receiving sensor data for a robot adjacent to a staircase. For each stair of the staircase, the method includes detecting, at a first time step, an edge of a respective stair of the staircase based on the sensor data. The method also includes determining whether the detected edge is a most likely step edge candidate by comparing the detected edge from the first time step to an alternative detected edge at a second time step, the second time step occurring after the first time step. When the detected edge is the most likely step edge candidate, the method includes defining, by the data processing hardware, a height of the respective stair based on sensor data height about the detected edge. The method also includes generating a staircase model including stairs with respective edges at the respective defined heights.

An example implementation for determining mechanically-timed footsteps may involve a robot having a first foot in contact with a ground surface and a second foot not in contact with the ground surface. The robot may determine a position of its center of mass and center of mass velocity, and based on these, determine a capture point for the robot. The robot may also determine a threshold position for the capture point, where the threshold position is based on a target trajectory for the capture point after the second foot contacts the ground surface. The robot may determine that the capture point has reached this threshold position and based on this determination, and cause the second foot to contact the ground surface.

A robot is provided. The robot includes a sensor, a driver, a communication interface, and a processor configured to acquire first context data through the sensor, receive second context data acquired by at least one other robot through the communication interface, identify at least one context data of the first context data and the second context data based on a collaboration scenario of the robot and the other robot, input the identified at least one context data to a predetermined task allocation algorithm related to the collaboration scenario to acquire task information corresponding to the robot, and control the driver based on the acquired task information.

A foothold position control system and method for a biped robot are provided. 1) A feasible collision-free path is planned by using a path planning algorithm; 2) an available foothold area of a swing foot is determined according to step-length constraints, movement capabilities, foot sizes, and center offsets of a biped robot; and 3) fuzzy processing is performed to determine a specific foothold position of the biped robot. Selection of suitable foothold positions on both sides of a path when a biped robot executes specific walking actions after finishing path planning is realized. The foothold position control system and method has the advantages of being simple and easy to implement, having low computational load and high speed, being capable of exerting extreme movement capabilities of different biped robots, enabling more flexible movement of the biped robots, and so on.

A humanoid robot and its balance control method and computer readable storage medium are provided. Expected accelerations of each of a sole and centroid of a humanoid robot corresponding to a current expected balance trajectory and an expected angular acceleration of the waist corresponding to the current expected balance trajectory are obtained based on current motion data of the sole, the centroid, and the waist, respectively first, then an expected angular acceleration of each joint meeting control requirements of the sole, the centroid, and the waist while the robot corresponds to the current expected balance trajectory is calculated based on an angular velocity of the joint, the expected accelerations of the waist, the sole, and the centroid, respectively, and then each joint of the robot is controlled to move at the obtained expected angular acceleration of the joint based on the angular displacement of the joint.