Method of parameters collaborative learning of multiple CAN node for industrial robots

Industrial robots usually divide some functions into modules in the form of multiple CAN nodes, set and use the same parameters to achieve specific motion control functions, and generally perform parameter learning through diagnostic services. In order to avoid all the CAN nodes to implement complex diagnostic protocols, the diagnostic protocols related to parameter learning are implemented on a single node, and the parameter learning and learning result verification of other nodes are dominated by dedicated CAN messages and protocols.It avoids the problem of repeated development of diagnostic protocols for multiple nodes. It is not necessary to modify the design of this method when adding or subtracting CAN nodes. It is also suitable for parameter collaborative learning of multiple CAN nodes in other CAN networks, and has strong versatility.