An optimization framework for simulation and kinematic control of Constrained Collaborative Mobile Agents (CCMA) system
This work addresses the control complexity in modular robotic systems for tasks like manipulation, though it appears incremental in applying optimization to a specific robotic configuration.
The authors tackled the problem of controlling a modular robotic system of multiple wheeled mobile agents constrained by a passive kinematic chain by developing an optimization framework for simulation and kinematic control, enabling flexible deployment and actuation schemes as demonstrated in simulations and experiments with 4-DOF to 6-DOF prototypes.
We present a concept of constrained collaborative mobile agents (CCMA) system, which consists of multiple wheeled mobile agents constrained by a passive kinematic chain. This mobile robotic system is modular in nature, the passive kinematic chain can be easily replaced with different designs and morphologies for different functions and task adaptability. Depending solely on the actuation of the mobile agents, this mobile robotic system can manipulate or position an end-effector. However, the complexity of the system due to presence of several mobile agents, passivity of the kinematic chain and the nature of the constrained collaborative manipulation requires development of an optimization framework. We therefore present an optimization framework for forward simulation and kinematic control of this system. With this optimization framework, the number of deployed mobile agents, actuation schemes, the design and morphology of the passive kinematic chain can be easily changed, which reinforces the modularity and collaborative aspects of the mobile robotic system. We present results, in simulation, for spatial 4-DOF to 6-DOF CCMA system examples. Finally, we present experimental quantitative results for two different fabricated 4-DOF prototypes, which demonstrate different actuation schemes, control and collaborative manipulation of an end-effector.