As robotics deployments grow from single-robot systems to large-scale, multi-robot environments, achieving reliable and efficient operations becomes increasingly challenging. Issues such as task allocation, traffic conflicts, interoperability, maintenance, incident management, and system-level visibility emerge as key barriers to scaling robotic solutions. This session will discuss how fleet management acts as a critical enabler for scaling robotics in real-world deployments. It will cover the core components of robot fleet management and explain how these elements work together to enable coordinated and efficient operations. The talk will also highlight open-source initiatives that are contributing to the standardization of fleet management for multi-vendor deployments. Attendees will gain insights into the key factors that enable scalable robotic systems through fleet management, as well as key considerations when evaluating fleet management solutions.
Harsh Vardhan Singh holds an M.S. degree in Computer Science from Georgia Institute of Technology with specialization in Machine Learning.
He is a Manager – Solution Architecture at eInfochips (An Arrow Company) where he leads the design and development of robotics and AI/ML-driven automation solutions. In addition to driving technical execution, he plays a key role in shaping customer engagement and expanding the robotics partnership ecosystem.
With over a decade of experience, Harsh has built and deployed robotics and AI-driven autonomous systems spanning ROS2, navigation, SLAM, computer vision, machine learning (DL/ML/RL), sensor fusion, and cloud technology. His experience covers a wide range of applications, including autonomous forklifts for pallet picking, autonomous mobile robots (AMRs), multi-robot fleet management systems, bin picking, automated palletization, and online bin packing. His expertise and leadership have contributed to a patent in depth camera benchmarking, and he has co-authored research papers published in leading IEEE conferences and workshops.
More recently, his work has focused on advancing humanoid and Physical AI capabilities by leveraging advanced AI techniques such as vision-language-action (VLA) models and imitation learning, enabling robots to perform complex manipulation tasks.
Schedule a 30-minute consultation with our Automotive Solution Experts
Schedule a 30-minute consultation with our Battery Management Solutions Expert
Schedule a 30-minute consultation with our Industrial & Energy Solutions Experts
Schedule a 30-minute consultation with our experts
