Optimal filtering in multi-agent robots using leader-follower formation

Multi-agent robots, working in a group and sharing intelligent information, have several advantages over a single agent robot such as simplicity in agent design, better performance, increased fault tolerance and spatially distributed sensing. Applications of such systems are abundant in various fields of engineering and sciences. Multi-agent robots using leader-follower formation comprises of a group of robots which share information and work together to complete a specific task. In this paper, we utilize a team of multi-agent robots having slow sampling time-periods to work together to achieve fast sampling time-period. This paper address the issue of designing finite impulse response (FIR) filters, using ℋ₂ and ℋ_∞ norm optimization, to minimize the effects of network time-delays, which usually occur in networked systems. An example is also presented to demonstrate the effectiveness of the presented approach.