One of the promising technologies to revolutionize the way AI works is Swarm Robotics. However, Swarm robotics applications in the real world are not without challenges.
The several challenges associated with Swarm robotics are:
- Limited scalability: Swarm robotics is far from being considered a mature technology due to the focus of researchers on some “basic” tasks, such as formation control and obstacle avoidance. The scalability of swarm robotics applications is always under control for a large number of simple robots to solve complex tasks.
- Communication challenges: Swarm robots face several challenges in real-world scenarios to exchange coordination messages across the swarm. Swarms need to be able to communicate with each other reliably and efficiently to complete tasks.
- Hardware limitations: Robots with such limitations, such as limited battery life and processing power, can limit the capabilities of swarm robotics systems.
- Lack of real-world applications: Real-world swarm applications are lacking in the literature on working with swarm algorithms. Only parts of swarm algorithms are used to refer to basic swarm behaviours. Swarm robots are successfully employed in a wide variety of common abstract missions that can be applied to real-world applications.
- Testing and evaluation: A need for a research platform to be used for testing and evaluating swarm behaviour, systems already on the market, and projects working on a specific market
- Communication challenges: In real-world scenarios, swarm robots face several challenges in exchanging coordination messages across the swarm. Swarms need to communicate with each other reliably and efficiently to complete tasks.
The implementation of swarm robotics in real-world applications is in its early stages. It faces several challenges with a wide range of issues and concerns.