Distributed sampled-data control of nonholonomic multi-robot systems with proximity networks
This work addresses coordination challenges for mobile robot swarms in applications like surveillance or logistics, representing an incremental advance by relaxing prior graph assumptions.
The paper tackles the distributed sampled-data control problem for nonholonomic multi-robot systems using proximity networks, providing sufficient conditions for synchronization without leaders and establishing the proportion of leaders needed to track desired signals, with conditions depending on neighborhood radius, maximum initial speed, and dwell time.
This paper considers the distributed sampled-data control problem of a group of mobile robots connected via distance-induced proximity networks. A dwell time is assumed in order to avoid chattering in the neighbor relations that may be caused by abrupt changes of positions when updating information from neighbors. Distributed sampled-data control laws are designed based on nearest neighbour rules, which in conjunction with continuous-time dynamics results in hybrid closed-loop systems. For uniformly and independently initial states, a sufficient condition is provided to guarantee synchronization for the system without leaders. In order to steer all robots to move with the desired orientation and speed, we then introduce a number of leaders into the system, and quantitatively establish the proportion of leaders needed to track either constant or time-varying signals. All these conditions depend only on the neighborhood radius, the maximum initial moving speed and the dwell time, without assuming a prior properties of the neighbor graphs as are used in most of the existing literature.