Control Algorithms for a Mobile Robot Application in a Fog Computing Environment

The growing demand of industrial, automotive and service robots presents a challenge to the centralized Cloud Robotics model in terms of privacy, security, latency, bandwidth, and reliability. Especially, mobile robots have limited on-board computational power which restricts their mission planning in autonomous applications. With the evolution of Fog computing, computations may be offloaded to Fog devices and/or smart gateway devices which together form a distributed computing platform in close proximity to the mobile robot. In this work, we demonstrate the application of Fog computing for mobile robots with a specific case study of color-based object detection, tracking and mapping in a confined area. The computations required for image processing are offloaded to the Fog devices via Fog nodes and the results are acquired back in real-time. The control algorithms for tracking predefined paths and mapping a pre- defined area are validated using a controlled mobile robot with an on-board camera and processing unit. Also, the effects of improvement in latency due to fog environment as compared to on-board computation on the mobile robot is demonstrated.