Challenges in Multi-domain Robot Swarm for Industrial Mapping and Asset Monitoring

Abstract

Heterogeneous systems integrating ground-mobile vehicle robots and drone UAVs to perform indoor mapping and explore complex operational environments such as industrial areas where the obstacles take places. Despite their potential to enable advanced autonomous exploration with self-reinforcement learning and navigation capabilities, these systems face multiple challenges related to communication, coordination, security, and landscape mapping. This paper discusses the challenges associated with implementing heterogeneous robot systems and examines relevant research articles that contribute to addressing them. Firstly, determining the most effective localization method in unstructured environments, where traditional navigation aids might be limited, poses a significant hurdle. Vision-based approaches for landing the drones on a mobile robot introduce complexities that require innovative solutions. We also need to address the communication challenges that demand real-time and secure data exchanges between vehicular and drone robot systems. Moreover, the limitations of GPS in indoor environments necessitate alternative positioning solutions. Additionally, coordinating leader-follower dynamics between drones and mobile robots requires sophisticated strategies to ensure smooth collaboration and effective mapping. This paper comprehensively examines these challenges and explores relevant research articles that contribute to addressing them, shedding light on potential solutions and avenues for future research.