A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to perform operations including obtaining a topological map including waypoints and edges. Each edge connects adjacent waypoints. The waypoints and edges represent a navigation route for the robot to follow. Operations include determining, that an edge that connects first and second waypoints is blocked by an obstacle. Operations include generating, using image data and the topological map, one or more alternate waypoints offset from one of the waypoints. For each alternate waypoint, operations include generating an alternate edge connecting the alternate waypoint to a waypoint. Operations include adjusting the navigation route to include at least one alternate waypoint and alternate edge that bypass the obstacle. Operations include navigating the robot from the first waypoint to an alternate waypoint along the alternate edge connecting the alternate waypoint to the first waypoint.

The operations of a computer-implemented method include obtaining a topological map of an environment including a series of waypoints and a series of edges. Each edge topologically connects a corresponding pair of adjacent waypoints. The edges represent traversable routes for a robot. The operations include determining, using the topological map and sensor data captured by the robot, one or more candidate alternate edges. Each candidate alternate edge potentially connects a corresponding pair of waypoints that are not connected by one of the edges. For each respective candidate alternate edge, the operations include determining, using the sensor data, whether the robot can traverse the respective candidate alternate edge without colliding with an obstacle and, when the robot can traverse the respective candidate alternate edge, confirming the respective candidate alternate edge as a respective alternate edge. The operations include updating, using nonlinear optimization and the confirmed alternate edges, the topological map.

A computer-implemented method when executed by data processing hardware causes the data processing hardware to perform operations. The operations include receiving a navigation route for a mobile robot. The navigation route includes a sequence of waypoints connected by edges. Each edge corresponds to movement instructions that navigate the mobile robot between waypoints of the sequence of waypoints. While the mobile robot is traveling along the navigation route, the operations include determining that the mobile robot is unable to execute a respective movement instruction for a respective edge of the navigation route due to an obstacle obstructing the respective edge, generating an alternative path to navigate the mobile robot to an untraveled waypoint in the sequence of waypoints, and resuming travel by the mobile robot along the navigation route. The alternative path avoids the obstacle.

The embodiment of the present disclosure provides a robot control method, a robot and a storage medium. In the embodiment of the present disclosure, the robot determines a position when the robot is released from being hijacked based on relocalization operation; determines a task execution area according to environmental information around the position when the robot is released from being hijacked; and afterwards executes a task within the task execution area. Thus, the robot may flexibly determine the task execution area according to the environment in which the robot is released from being hijacked, without returning to the position when the robot is hijacked, to continue to execute the task, then acting according to local conditions is realized and the user requirements may be met as much as possible.

A legged robot motion control method includes: acquiring centroid state data of a spatial path start point and a spatial path end point of a motion path; determining a target landing point of afoot of the legged robot in the motion path based on the spatial path start point and the spatial path end point; determining a change relationship between a centroid position change coefficient and a foot contact force based on the centroid state data; selecting, under constraint of a constraint condition set, a target centroid position change coefficient that meets the change relationship; the constraint condition set including a spatial landing point constraint condition; determining a target motion control parameter according to the target centroid position change coefficient and the target landing point of the foot; and controlling, based on the target motion control parameter, the legged robot to perform motion according to the motion path.

To provide an information processing apparatus, an information processing method, and a program that allow smooth movement of a mobile body. The information processing apparatus includes a position information acquisition unit, a posture information acquisition unit, a generation unit, and a mobile body controller. The position information acquisition unit acquires position information of a mobile body. The posture information acquisition unit acquires posture information of the mobile body. The generation unit generates a target trajectory to a target point, the target trajectory including a plurality of waypoints each including waypoint information including a position command value and a posture command value for the mobile body. The mobile body controller extracts, from the plurality of waypoints, waypoints existing within a threshold distance from the mobile body using the position information and the position command value, selects, from the extracted waypoints, a waypoint having a smallest difference between the posture command value of the waypoint and the posture information, and sets the waypoint as a reference point.

A gait planning method and a robot using the same as well as a computer readable storage medium are provided. The method includes: determining a reference leg length l.sub.0 and a leg length variation range A of a robot; performing a trajectory planning on a length of at least one of the legs of the robot using; an equation including the reference leg length, the leg length variation range, and a preset recurrent excitation function of a time variable t. In this manner, the trajectory planning for the leg length of the robot during motion is performed according to the characteristics of motion scene such as robot jumping or running so that the change of the leg length of the robot is adapted to the motion process, which greatly improves the stability of the robot in the motion scene such as jumping or running.

Disclosed herein are a robot that generates a map and configures a correlation of nodes, based on multi sensors and artificial intelligence, and that moves based on the map, and a method of generating a map, and the robot according to an embodiment generates a pose graph comprised of LiDAR branch, visual branch, and backbone, and the LiDAR branch includes one or more of the LiDAR frames, the visual branch includes one or more of the visual frames, and the backbone includes two or more frame nodes registered with any one or more of the LiDAR frames or the visual frames, and to generate a correlation between nodes in the pose graph.

On-floor obstacle detection using an RGB-D camera is disclosed. An obstacle on a floor is detected by receiving an image including depth channel data and RGB channel data through the RGB-D camera, estimating a ground plane corresponding to the floor based on the depth channel data, obtaining a foreground of the image corresponding to the ground plane based on the depth channel data, performing a distribution modeling on the foreground of the image based on the RGB channel data to obtain a 2D location of the obstacle, and transforming the 2D location of the obstacle into a 3D location of the obstacle based on the depth channel data.

Provided is an information processing apparatus that processes information regarding a path of a mobile robot.

The information processing apparatus includes a management section that manages path information for each path, the path information including postural stability information acquired when the mobile robot traverses the path. The postural stability information includes at least one of a variance of a position of center of gravity or a postural variance acquired during travel of the mobile robot in the path. Also, the postural stability information includes a CoP control quantity that includes a deviation between a target CoP and an actual measured value of the mobile robot whose walking is controlled on the basis of a ZMP. Also, the postural stability information further includes a landing position correction quantity that includes an error between a planned floor touching point and an actual measured value of the mobile robot that walks with multiple legs.