Sensing and Communication Mechanisms for Advanced Robotics and Complex Cyber-Physical Systems

Robotics and Automation have been pertinent and rigorously active fields of research and advancement for the last few decades, with the advent of cheaper and improved software and scalable hardware accelerating the progress. Self-driving cars, an emerging branch of cyber-physical systems, have become increasingly common and collaborative robots are being utilized in industries to work to fulfill activities that cannot be controlled by a single robot. Such autonomous vehicles and robotic systems are reliant heavily on sensing and communication with their environments and other agents, including robots, machinery, and humans. Progress in adopting better sensing and perception technologies has produced breakthroughs in facilitating autonomous manufacturing and robotic systems, making them more real than fiction. Mobile robots are expected to navigate and perform dedicated tasks in uncertain conditions and ill-defined environments, in basics they are required to avoid any possible dangerous obstacles in their path, recognize task agents, and interact with their environment. Several technologies including lidar sensors, ultrasonic sensors, odometers, etc., are utilized for “Simultaneous Localization and Mapping” or SLAM applications which will be discussed within this chapter. In many manufacturing industries, robotic manipulators are utilized in assembly lines to interact with objects on conveyor belts and production areas. These situations are challengingly dynamic and thus require efficient control and communication protocols. Autonomous vehicles and self-driving cars are also one arena in which technology is pushing the scope of sensing and perception. Integration of sensor networks with robotic agents is important for effective application, as the environment is rich in information and efficient implementation requires simultaneous processing of multiple environmental vectors. The study and application of perception, localization, cognition, and navigation can be done in either a simulation environment or using robotic platforms and hardware. The limits to any robotic system are its ability to perceive its environment on its own and relay information between multiple agents, including humans. Thus, autonomous interfacing systems with efficient sensor and communication technologies are necessary to enable a system to operate in any environment, which is a complex task. This chapter will follow the recent discussions and research on such technologies and their applications. The sub-sections provide details into the design, control, and implementation of communication, sensing, and perception practices for robotic systems.