Mobile robot, and control method of mobile robot

A control method of a mobile robot, the method comprising:

• an experience information generating step of obtaining current state information through sensing during traveling, and, based on a result of controlling an action according to action information selected by inputting the current state information to a predetermined action control algorithm for docking, generating one experience information that comprises the state information and the action information;
• an experience information collecting step of storing a plurality of experience information by repeatedly performing the experience information generating step;
• and
• a learning step of learning the action control algorithm based on the plurality of experience information.

A control method of a mobile robot, the method comprising:

• an experience information generating step of obtaining nth state information through sensing in a state at an nth point in time during traveling, and, based on a result of controlling an action according to nth action information selected by inputting the nth state information to a predetermined action control algorithm for docking, generating nth experience information that comprises the nth state information and the nth action information;
• an experience information collecting step of storing first to pth experience information by repeatedly performing the experience information generating step in ab order from a case where n is 1 to a case where n is p;
• and
• a learning step of learning the action control algorithm based on the first to pth experience information,
• wherein p is a natural number equal to or greater than 2, and a state at a p+1th point in time is a docking complete state.

A control method of a mobile robot, the method comprising:

• an experience information generating step of obtaining nth state information through sensing in a state at an nth point in time during traveling, based on a result of controlling an action according to nth action information selected by inputting the nth state information to a predetermined action control algorithm for docking, obtaining n+1th reward score, and generating nth experience information that comprises the nth state information, the nth action information, and the n+1th reward score;
• an experience information collecting step of storing first to pth experience information by repeatedly performing the experience information generating step in ab order from a case where n is 1 to a case where n is p;
• and
• a learning step of learning the action control algorithm based on the first to pth experience information,
• wherein p is a natural number equal to or greater than 2, and a state at a p+1th point in time is a docking complete state.