Approximation-based control and avoidance of a mobile base with an onboard arm for MARS greenhouse operation

MARS greenhouse needs mobile robots with on-board arms, that are capable of navigating autonomously in the greenhouse, performing tasks such as carrying plant trays, farming, harvesting, plucking fruits and vegetables and so on. An adaptive neural net (NN) is used for coordinated motion control of base and arm using Lyapunov's approach. A one-layer NN based controller is designed to estimate the unknown dynamics of the system after the incorporation of nonholonomic constraints. This approach provides an inner loop that accounts for possible motion of the arm, with changing loads, while the base is carrying out a task. The case of maintaining a desired course and speed or tracking a desired Cartesian trajectory as the arm moves to its desired orientation with a load is considered. Outer loops are designed not only to avoid both stationary and moving obstacles but also to navigate the mobile base with the onboard arm along the path. The net result is a base plus arm motion controller that is capable of achieving a coordinated motion of the base plus arm in the presence of uncertain dynamics, load and the environment.