Supervised Reinforcement Learning for ULV Path Planning in Complex Warehouse Environment

Algorithm 1

The Training Procedure of the SDRL.

Input: Expert data, initial parameters and ;

fordo

 Update the discriminator by ascending the stochastic gradient;

 Update the internal rewards and external rewards ;

 Update the value function by ;

 Update the policy of the DRL by ;

end