Robot swarms are designed to work together as a collective unit, leveraging their individual capabilities to achieve tasks that would be difficult or impossible for a single robot.

Centralized architectures are not typically used in robot swarms due to their lack of scalability and resilience. Instead, decentralized and swarm intelligence approaches are more commonly employed.

Decentralized architectures allow robot swarms to scale more easily to larger numbers of robots, as each robot operates autonomously and communicates only with its neighbors.

Task allocation and coordination are critical challenges in cooperative robotics, as multiple robots must work together efficiently to achieve a common goal.

Behavior-based architectures allow complex tasks to be broken down into a set of simpler behaviors, which can be executed by individual robots or groups of robots.

Self-driving cars are typically considered a form of autonomous robotics, rather than cooperative robotics, as they do not involve multiple robots working together.

Robot swarms offer increased flexibility and adaptability, as they can be easily reconfigured and deployed to different environments and tasks.

Swarm intelligence algorithms, such as particle swarm optimization and ant colony optimization, are often used to achieve coordination in robot swarms, as they allow robots to collectively find optimal solutions to complex problems.

Limited bandwidth and unreliable communication channels are major challenges in designing communication protocols for robot swarms, as they can lead to delays and errors in information exchange.

GPS sensors are not typically used in robot swarms due to their limited accuracy and reliability in indoor environments and dense formations.

Decentralized approaches to motion planning and control allow robot swarms to scale more easily to larger numbers of robots, as each robot can independently plan and execute its own movements.

All of the above challenges are commonly encountered in the development of cooperative robotics systems.

Swarm robotics research encompasses all of these goals, aiming to advance the field in various aspects.

While robot swarms have been proposed for various applications, space exploration and planetary missions are not typically considered feasible due to the extreme environmental conditions and communication challenges.

Cooperative robotics can improve productivity and efficiency in manufacturing and assembly tasks by enabling multiple robots to work together in a coordinated manner, reducing production time and increasing output.