Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a solution to the problem of steering a group of real omnidirectional mobile robots along a given path, while maintaining a desired formation pattern. This problem can be divided into a leader agent subproblem and a follor agent subproblem such that a leader agent follows a given path and each follor agent tracks a trajectory, estimated by using the leaderpsilas information. ,  exploit nonlinear model predictive control (NMPC) as a local control law for real-world experiments due to its advantages of taking the robot constraints and future information into account. To solve the path following problem for the leader agent,  propose to integrate the rate of progression of a virtual vehicle to be follod along that path into the local cost function of NMPC. After the open-loop optimization problem is solved, the optimal rate of progression at each time step in the future is obtained. This information and the leaderpsilas current state are broadcasted to all follor agents. With respect to a desired formation configuration and a reference path, each follor agent can estimate its own reference trajectory by using the leaderpsilas information and its time stamp. NMPC is also employed as a local control law to steer the follor agent to track that reference trajectory. Our approach was validated by experiments using three omnidirectional mobile robots.
['Kiattisin Kanjanawanishkul', 'Andreas Zell']
I am writing a research paper on a idea A model-predictive approach to formation control of omnidirectional mobile robots
[{"from": "human", "value": "I am writing a research paper on a idea A model-predictive approach to formation control of omnidirectional mobile robots"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a solution to the problem of steering a group of real omnidirectional mobile robots along a given path, while maintaining a desired formation pattern. This problem can be divided into a leader agent subproblem and a follor agent subproblem such that a leader agent follows a given path and each follor agent tracks a trajectory, estimated by using the leaderpsilas information. ,  exploit nonlinear model predictive control (NMPC) as a local control law for real-world experiments due to its advantages of taking the robot constraints and future information into account. To solve the path following problem for the leader agent,  propose to integrate the rate of progression of a virtual vehicle to be follod along that path into the local cost function of NMPC. After the open-loop optimization problem is solved, the optimal rate of progression at each time step in the future is obtained. This information and the leaderpsilas current state are broadcasted to all follor agents. With respect to a desired formation configuration and a reference path, each follor agent can estimate its own reference trajectory by using the leaderpsilas information and its time stamp. NMPC is also employed as a local control law to steer the follor agent to track that reference trajectory. Our approach was validated by experiments using three omnidirectional mobile robots."}]