Of late, a lot of natural calamities are disrupting the daily life: bush-fires in Australia, forest fires in California and flooding of thirteen Indian states, Venice and several regions of the the United Kingdom owing to torrential rainfall. To some extent, our negligence towards the environment is to blame. The challenge here is that the environment to be monitored is often large and usually not feasible to be covered with static sensors. A passive solution to this could be to use robots as mobile sensor nodes, given their agility, to simply observe and transmit the data to a base station. But why stop there when the robots can also be endowed with decision making capabilities using artificial intelligence (AI) algorithms to actively process incoming data.
To this end, announcing the official launch of the book titled “Multi-robot Exploration for Environment Monitoring” which presents a one-of-a-kind resource constrained perspective. Herein, the challenges faced during the deployment of mobile robots for
environmental monitoring are discussed. For instance, often robots are destined to deal with resource allocation problems, which has been described in-depth and an attempt has been made to provide solutions for it. Also, the book gives an intuitive crash course on non-parametric Bayesian inference often used for environmental monitoring. In doing so, it opens up new arenas for further research along these lines.
Originally published at http://planetrescue101.design.blog on November 15, 2019.