Geometry-based Parking Assistance using Sensor Fusion for Robots with Hardware Schemes

Mobile robots parking in indoor environments, trending towards complex problems, has motivated the development of new hardware computational paradigms. In this paper, we present a novel and effective research for addressing parking assistance in slot identification based on the geometry of a mobile robots using sensor data fusion with hardware schemes. This paper has been abstracted into three levels. Initially, the geometry of the mobile robots was analyzed using multi-sensory fusion at the gateway and parking slots of the indoor environment. A heuristic algorithm was developed to analyze the vehicle geometry patterns. Reconfigurable computing architectures have been developed for geometry analysis with respect to measurements of individuals or groups of robots as leader-follower and rendezvous approaches. The next level of the proposed algorithm estimates the availability of parking slots as per mobile robots geometry using a customized accelerator approach. Mobile robots navigate parking spaces using parking assistance and environmental maps. Parking assistance is integrated with direction-based path planning and odometer techniques are embedded in a known environmental navigation map. A Zynq XC7Z020-CLG484-1 Field Programmable Gate Array (FPGA) was deployed to validate and implemented the design using Xilinx Vivado 2017.4. This paper presents essential information for indoor logistics industries, hospital services, and domestic services at home.