Distributed coordinated path following using guiding vector fields
This addresses the need for efficient, repetitive tasks like environmental monitoring in robotics, but it is incremental as it builds on existing path-following and coordination methods.
The paper tackled the problem of scalable coordinated motion control for multiple mobile robots by designing a guiding vector field to guide robots along different desired paths while coordinating their motions, with simulations up to fifty robots and outdoor experiments validating the results.
It is essential in many applications to impose a scalable coordinated motion control on a large group of mobile robots, which is efficient in tasks requiring repetitive execution, such as environmental monitoring. In this paper, we design a guiding vector field to guide multiple robots to follow possibly different desired paths while coordinating their motions. The vector field uses a path parameter as a virtual coordinate that is communicated among neighboring robots. Then, the virtual coordinate is utilized to control the relative parametric displacement between robots along the paths. This enables us to design a saturated control algorithm for a Dubins-car-like model. The algorithm is distributed, scalable, and applicable for any smooth paths in an $n$-dimensional configuration space, and global convergence is guaranteed. Simulations with up to fifty robots and outdoor experiments with fixed-wing aircraft validate the theoretical results.