The present invention concerns a novel leg mechanism for quadrupedal locomotion. This design engages a linkage to couple assembly that only requires a single degree of actuation. The topological arrangement of the system produces a foot trajectory that is well-suited for dynamic gaits including trot-running, bounding, and galloping.

The present invention concerns a novel leg mechanism for quadrupedal locomotion. This design engages a linkage to couple assembly that only requires a single degree of actuation. The topological arrangement of the system produces a foot trajectory that is well-suited for dynamic gaits including trot-running, bounding, and galloping.

A method of controlling a robot includes: obtaining an inertia matrix and a slack variable of the robot, and determining a momentum equation of the robot according to the inertia matrix and the slack variable; obtaining reference joint angles corresponding to a reference action of the robot; determining an optimization objective function of the momentum equation according to a first preset weight coefficient of the slack variable and a second preset weight coefficient of the reference joint angles; and determining joint angles of the robot according to the optimization objective function, and driving the robot to move according to the joint angles of the robot.

A method of controlling a robot includes: obtaining an inertia matrix and a slack variable of the robot, and determining a momentum equation of the robot according to the inertia matrix and the slack variable; obtaining reference joint angles corresponding to a reference action of the robot; determining an optimization objective function of the momentum equation according to a first preset weight coefficient of the slack variable and a second preset weight coefficient of the reference joint angles; and determining joint angles of the robot according to the optimization objective function, and driving the robot to move according to the joint angles of the robot.

A jumping motion control method for a biped robot includes: before feet of the biped robot leaves a support surface, estimating a motion trajectory of the biped robot that leaves the support surface according to a period of time when the biped robot stays or flips in the air; calculating a first motion angle of each joint of legs of the biped robot according to the motion trajectory and inverse kinematics; determining a constraint condition according to a motion type to which an action to be performed by the biped robot corresponds; optimizing the first motion angles according to the constraint condition to obtain a second motion angle of each joint of legs of the biped robot; and controlling a jumping motion of the biped robot according to the second motion angles.

A jumping motion control method for a biped robot includes: before feet of the biped robot leaves a support surface, estimating a motion trajectory of the biped robot that leaves the support surface according to a period of time when the biped robot stays or flips in the air; calculating a first motion angle of each joint of legs of the biped robot according to the motion trajectory and inverse kinematics; determining a constraint condition according to a motion type to which an action to be performed by the biped robot corresponds; optimizing the first motion angles according to the constraint condition to obtain a second motion angle of each joint of legs of the biped robot; and controlling a jumping motion of the biped robot according to the second motion angles.

A method of constrained mobility mapping includes receiving from at least one sensor of a robot at least one original set of sensor data and a current set of sensor data. Here, each of the at least one original set of sensor data and the current set of sensor data corresponds to an environment about the robot. The method further includes generating a voxel map including a plurality of voxels based on the at least one original set of sensor data. The plurality of voxels includes at least one ground voxel and at least one obstacle voxel. The method also includes generating a spherical depth map based on the current set of sensor data and determining that a change has occurred to an obstacle represented by the voxel map based on a comparison between the voxel map and the spherical depth map. The method additional includes updating the voxel map to reflect the change to the obstacle.

A method of constrained mobility mapping includes receiving from at least one sensor of a robot at least one original set of sensor data and a current set of sensor data. Here, each of the at least one original set of sensor data and the current set of sensor data corresponds to an environment about the robot. The method further includes generating a voxel map including a plurality of voxels based on the at least one original set of sensor data. The plurality of voxels includes at least one ground voxel and at least one obstacle voxel. The method also includes generating a spherical depth map based on the current set of sensor data and determining that a change has occurred to an obstacle represented by the voxel map based on a comparison between the voxel map and the spherical depth map. The method additional includes updating the voxel map to reflect the change to the obstacle.

An example implementation includes determining a force allocation for at least one foot of a legged robotic device, where the legged robotic device includes two feet coupled to two legs extending from a body of the legged robotic device. The implementation also includes determining a change in mass distribution of the legged robotic device, and based on the determined change in mass distribution, determining a force and a torque on the body of the legged robotic device with respect to a ground surface. The implementation also includes updating the determined force allocation for the at least one foot of the two feet based on the determined force and torque. The implementation also includes causing the at least one foot to act on the ground surface based on the updated force allocation.

An example implementation includes determining a force allocation for at least one foot of a legged robotic device, where the legged robotic device includes two feet coupled to two legs extending from a body of the legged robotic device. The implementation also includes determining a change in mass distribution of the legged robotic device, and based on the determined change in mass distribution, determining a force and a torque on the body of the legged robotic device with respect to a ground surface. The implementation also includes updating the determined force allocation for the at least one foot of the two feet based on the determined force and torque. The implementation also includes causing the at least one foot to act on the ground surface based on the updated force allocation.