The present disclosure provides a stair climbing gait planning method and an apparatus and a robot using the same. The method includes: obtaining first visual measurement data through a visual sensor of the robot; converting the first visual measurement data to second visual measurement data; and performing a staged gait planning on a process of the robot to climb the staircase based on the second visual measurement data. Through the method, the visual measurement data is used as a reference to perform the staged gait planning on the process of the robot to climb the staircase, which greatly improves the adaptability of the robot in the complex scene of stair climbing.

A worm-like soft crawling robot driven by an exergonic chemical reaction, including a body system, an exothermic reaction system and a vacuum system. The body system includes a left head shell, a left flexible body shell, a left reaction chamber, a right reaction chamber, a right flexible body shell and a right head shell. Elastic transmission parts are installed in the flexible body shells in a matched way. The exothermic reaction system includes chemical fuel storage units and exothermic reaction stimulation devices. The vacuum system includes vacuum suction cups, vacuum exhaust tubes and vacuum pumps.

A worm-like soft crawling robot driven by an exergonic chemical reaction, including a body system, an exothermic reaction system and a vacuum system. The body system includes a left head shell, a left flexible body shell, a left reaction chamber, a right reaction chamber, a right flexible body shell and a right head shell. Elastic transmission parts are installed in the flexible body shells in a matched way. The exothermic reaction system includes chemical fuel storage units and exothermic reaction stimulation devices. The vacuum system includes vacuum suction cups, vacuum exhaust tubes and vacuum pumps.

An insect-like jumping-flying robot is provided, which includes a flying module, a driving module and biomimetic bouncing legs. The flying module provides flying power via a propeller and a miniature model airplane motor, and front wings and rear wings provide lift, and moment required for attitude change. The driving module provides power with high power density via a brushless motor and is provided with two stages of deceleration to amplify the torque provided by the brushless motor. The first stage of deceleration is performed by a synchronous wheel set, and the second stage of deceleration is performed by a gear set. A driving push rod is used to transmit the power provided by the brushless motor to the biomimetic bouncing legs.

A walking vehicle including a chassis and a plurality of wheel-leg components is described. The plurality of wheel-leg components are collectively operable to provide wheeled locomotion and walking locomotion.

A robot has an electronic surveillance system embedded within a chassis disposed between two wheels. The wheels include a main body and a plurality of treads. The treads are generally disposed radially around the main body and extend distally from outer portion of the main body. The main body generally defines a plurality of compression cells and may present a substantially frustoconical outer surface.

A robot has an electronic surveillance system embedded within a chassis disposed between two wheels. The wheels include a main body and a plurality of treads. The treads are generally disposed radially around the main body and extend distally from outer portion of the main body. The main body generally defines a plurality of compression cells and may present a substantially frustoconical outer surface.

A computer-implemented gait planning method includes: determining a pitch angle between a foot of the robot and a support surface where the robot stands; determining a support point on a sole of the foot according to the pitch angle; calculating an ankle-foot position vector according to the support point, wherein the ankle-foot position vector is a position vector from an ankle of the robot to a support point on a sole of the foot; calculating a magnitude of change of an ankle position according to the pitch angle and the ankle-foot position vector; and obtaining a compensated ankle position by compensating the ankle position according to the magnitude of change of the ankle position.

A computer-implemented gait planning method includes: determining a pitch angle between a foot of the robot and a support surface where the robot stands; determining a support point on a sole of the foot according to the pitch angle; calculating an ankle-foot position vector according to the support point, wherein the ankle-foot position vector is a position vector from an ankle of the robot to a support point on a sole of the foot; calculating a magnitude of change of an ankle position according to the pitch angle and the ankle-foot position vector; and obtaining a compensated ankle position by compensating the ankle position according to the magnitude of change of the ankle position.

Systems and methods for determining movement of a robot about an environment are provided. A computing system of the robot (i) receives information including a navigation target for the robot and a kinematic state of the robot; (ii) determines, based on the information and a trajectory target for the robot, a retargeted trajectory for the robot; (iii) determines, based on the retargeted trajectory, a centroidal trajectory for the robot and a kinematic trajectory for the robot consistent with the centroidal trajectory; and (iv) determines, based on the centroidal trajectory and the kinematic trajectory, a set of vectors having a vector for each of one or more joints of the robot.