1 research outputs found
Building an Integrated Mobile Robotic System for Real-Time Applications in Construction
One of the major challenges of a real-time autonomous robotic system for
construction monitoring is to simultaneously localize, map, and navigate over
the lifetime of the robot, with little or no human intervention. Past research
on Simultaneous Localization and Mapping (SLAM) and context-awareness are two
active research areas in the computer vision and robotics communities. The
studies that integrate both in real-time into a single modular framework for
construction monitoring still need further investigation. A monocular vision
system and real-time scene understanding are computationally heavy and the
major state-of-the-art algorithms are tested on high-end desktops and/or
servers with a high CPU- and/or GPU- computing capabilities, which affect their
mobility and deployment for real-world applications. To address these
challenges and achieve automation, this paper proposes an integrated robotic
computer vision system, which generates a real-world spatial map of the
obstacles and traversable space present in the environment in near real-time.
This is done by integrating contextual Awareness and visual SLAM into a ground
robotics agent. This paper presents the hardware utilization and performance of
the aforementioned system for three different outdoor environments, which
represent the applicability of this pipeline to diverse outdoor scenes in near
real-time. The entire system is also self-contained and does not require user
input, which demonstrates the potential of this computer vision system for
autonomous navigation