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This paper presents a layered control approach for real-time trajectoryplanning and control of robust cooperative locomotion by two holonomicallyconstrained quadrupedal robots. A novel interconnected network of reduced-ordermodels, based on the single rigid body (SRB) dynamics, is developed fortrajectory planning purposes. At the higher level of the control architecture,two different model predictive control (MPC) algorithms are proposed to addressthe optimal control problem of the interconnected SRB dynamics: centralized anddistributed MPCs. The distributed MPC assumes two local quadratic programs thatshare their optimal solutions according to a one-step communication delay andan agreement protocol. At the lower level of the control scheme, distributednonlinear controllers are developed to impose the full-order dynamics to trackthe prescribed reduced-order trajectories generated by MPCs. The effectivenessof the control approach is verified with extensive numerical simulations andexperiments for the robust and cooperative locomotion of two holonomicallyconstrained A1 robots with different payloads on variable terrains and in thepresence of disturbances. It is shown that the distributed MPC has aperformance similar to that of the centralized MPC, while the computation timeis reduced significantly.

Layered Control for Cooperative Locomotion of Two Quadrupedal Robots: Centralized and Distributed Approaches