Redundant robot joint acceleration planning method, redundant robot using the same, and computer readable storage medium

A redundant robot, comprising:

• a processor;
• a memory coupled to the processor;
• and
• one or more computer programs stored in the memory and executable on the processor;
• wherein, the one or more computer programs comprise:
• instructions for receiving a joint acceleration planning request, wherein the joint acceleration planning request carries an optimization target, a sampling period, an end Cartesian space speed at time k+1, and a joint parameter set of a plurality of target joints of the robot at time k;
• instructions for obtaining a quadratic programming function library, and obtaining an optimization objective function, a joint acceleration inequation constraint function and a joint acceleration equation constraint function corresponding to the optimization target from the quadratic programming function library, wherein the optimization objective function is an objective function obtained based on the upper and lower limits of the optimization target and a Euclidean distance algorithm;
• and
• instructions for obtaining a joint acceleration planning result by performing a quadratic optimization solving on a joint acceleration of each of the target joints of the robot at time k according to the end Cartesian space speed at time k+1, the joint parameter set of the target joints of the robot at time k, the sampling period, the optimization objective function, the joint acceleration inequation constraint function, and the joint acceleration equation constraint function;
• wherein when the optimization target is a joint position. the optimization objective function is determined by:
• determining the joint position of the i-th target joint at time k+1 according to the joint position of the i-th target joint at time k, the joint speed of the i-th target joint at time k, the joint acceleration of the i-th target joint at time k, and the sampling period;
• obtaining a position Euclidean distance of the i-th target joint at time k+1 by performing a Euclidean distance calculation on a difference value between the joint position of the i-th target joint at time k+1 and upper and lower limits of the joint position of the i-th target joint:
• obtaining a square value of an average value of the upper and lower limits of the joint position of the i-th target joint by performing a squaring calculation on an average value of the upper and lower limits of the joint position of the i-th target join;
• obtaining a position Euclidean distance ratio of the i-th target joint at time k+1 by dividing the position Euclidean distance of the i-th target joint at time k+1 by the square value of the average value of the upper and lower limits of the joint position of the i-th target joint;
• obtaining a second objective function by summing the position Euclidean distance ratios of all the target joints at time k+1;
• and
• obtaining the optimized objective function when the optimization target is the joint position by performing a minimum value solving on the second objective function.

A non-transitory computer readable storage medium for storing one or more computer programs, wherein the one or more computer programs comprise:

• instructions for receiving a joint acceleration planning request, wherein the joint acceleration planning request carries an optimization target, a sampling period, an end Cartesian space speed at time k+1, and a joint parameter set of a plurality of target joints of the robot at time k;
• instructions for obtaining a quadratic programming function library, and obtaining an optimization objective function, a joint acceleration inequation constraint function and a joint acceleration equation constraint function corresponding to the optimization target from the quadratic programming function library, wherein the optimization objective function is an objective function obtained based on the upper and lower limits of the optimization target and a Euclidean distance algorithm;
• and
• instructions for obtaining a joint acceleration planning result by performing a quadratic optimization solving on a joint acceleration of each of the target joints of the robot at time k according to the end Cartesian space speed at time k+1, the joint parameter set of the target joints of the robot at time k, the sampling period, the optimization objective function, the joint acceleration inequation constraint function, and the joint acceleration equation constraint function;
• wherein when the optimization target is a joint angle, the optimization objective function is determined by:
• obtaining a joint angle change speed of the i-th target joint at time k by performing a joint angle change speed calculation according to the joint speed of the i-th target joint at time k;
• obtaining a joint angle change acceleration of the i-th target joint at time k by performing a joint angle change acceleration calculation according to the joint acceleration of the i-th target joint at time k:
• determining the joint angle of the i-th target joint at time k+1 according to the joint angle of the i-th target joint at time k, the joint angle change speed of the i-th target joint at time k, and the joint angle change acceleration of the i-th target joint at time k, and the sampling period;
• obtaining an angular Euclidean distance of the i-th target joint is at time k+1 by performing a Euclidean distance calculation on the joint angle of the i-th target joint at time k+1 and an average value of upper and lower limits of the joint angle of the i-th target joint;
• obtaining a square value of a difference value between the upper and lower limits of the joint angle of the i-th target joint by performing a square calculation on the difference value of the upper and lower limits of the joint angle of the i-th target joint;
• obtaining an angular Euclidean distance ratio of the i-th target joint at time k+1 by dividing the angular Euclidean distance of the i-th target joint at time k+1 by the square value of the difference value between the upper and lower limits of the joint angle of the i-th target joint;
• obtaining a fifth objective function by summing the angular Euclidean distance ratios of all the target joints at time k+1;
• and
• obtaining the optimized objective function when the optimization target is the joint angle by performing a minimum value solving on the fifth objective function.