Raj Mohan, CTO & Co-Founder, ANSCER Robotics

Raj Mohan is the CTO and a Co-founder at ANSCER Robotics, based in Bengaluru, Karnataka. His high school years were when his interest in robotics was sparked, especially inspired by Science fiction movies. This led him to pursue his Bachelor’s degree in Electronics and Communication from Government Engineering College, Thrissur, followed by his MTech in Robotics and Automation from Amrita Vishwa Vidhyapeetham, Kollam, Kerala. Robotics comes easily to Raj, who was a university topper and won a gold medal for ranking first in his Master’s program.


Manufacturing production accounts for 78% of India’s total industrial output and research shows the sector has the potential to reach a market size of $1 trillion by 2025. But while this rapid pace of growth is an indication of upcoming opportunities, it cannot be achieved without first ensuring the optimization of workforce efficiency and management of labour-intensive activities. 

This is where the field of robotics steps in, bringing about a massive shift by helping companies and workforces migrate away from mundane, repetitive tasks to minimize errors, provide round-the-clock productivity, and improve work conditions for employees. All in all, robotics has the capability to make industrial manufacturing and operations in India and across the globe a lot more seamless. 

Locomotive robot systems – commonly referred to as mobile robots – are becoming increasingly popular across different business sectors due to their ability to carry out strenuous and labour-intensive tasks with little or no human involvement. These evolved from traditional manual carts and trolleys, which required employees to tug around the shop floor, not only causing ergonomic risks to workers but also non value-added travel and inefficiencies in supply chain management. Mobile robots, however, use a combination of artificial intelligence (AI), sensors and physical elements, such as wheels, tracks and legs, to move around the factory floor to complete various material handling tasks. Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) are two broad categories of locomotive robots that exist today. 

AGV technology requires external guidance such as magnetic strips, wires or sensors installed on the environment’s floor, which leads to an inflexible system that is both expensive and difficult to adjust as operational needs change. Setting up an AGV often requires facility changes to develop pre-planned paths that the robot can follow. Additionally, any obstacle in an AGV’s path makes the robot halt to a stop. AMRs, in contrast, are more advanced technology, capable of intelligently moving through and exploring a new environment without human intervention, and even manoeuvring around obstacles. This makes them the preferred choice for material movement needs, as they are easy and quick to deploy, reduce operational costs. And increase efficiency – all without needing to make any major changes to the existing floor layout.

Autonomous Mobile Robots have transformed internal mobility by taking care of specialized processes like transporting inventory and products across an environment, lifting pallets and shelves, tugging trolleys, conveyor integration, and even working with collaborative robot arm fixtures. This means they can be integrated in virtually any material handling application.

The demand and requirement for AMRs has been especially increasing in India after the onset of the COVID-19 pandemic, which disrupted several inherently labour-intensive operations. Companies across various sectors including but not limited to manufacturing, automotive, electronics, e-commerce, FMCG, and pharmaceuticals, have realised that deploying robotics solutions can help them continue operations even when they are functioning with a limited workforce or stringent hygiene measures. 

They have enabled businesses to easily manage demand surges even with limited or unreliable labour forces. Even HoReCa players and hospitals have started adopting AMR solutions to safely transport medicines, food etc., all the while reducing human contact and involvement as much as possible, and simultaneously increasing efficiency.

As more attention is rightfully given to employee working conditions, businesses are making use of AMRs to reduce ergonomic risks for their labourers and reduce their manual workload, especially for tasks that are time and labour-intensive. In sectors such as manufacturing, healthcare, and automotive, among others, employees tend to have longer hours and very strenuous jobs. Research has shown that this impacts their health adversely, often causing problems like scoliosis, weight gain, eyesight issues, and a host of other ergonomic issues. 

Incorporating robots or automating a few systems can help eliminate both physical and mental stress, not only improving working conditions but also the overall health and well-being of employees. Additionally, incorporating robotic technology also encourages businesses to invest in the upskilling of their workforce and designate them to more engaging and creative tasks, leaving the mundane work to robots. This, in turn, has a direct impact on boosting employee morale and improving attrition rates, which saves valuable time – and money – that would otherwise be spent on the constant pursuit and training of new workers.

In short, autonomous mobile robots are helping industries to create the supply chain of the future by helping industry players decrease long-term costs, complement and upskill their workforce, increase employee productivity, and reduce errors. AMRs optimize picking, sorting, and storing times, and increase access to difficult or dangerous locations.

The robotics revolution is here in full swing and things will only get better when manufacturers learn how to implement this exciting technology. Robotics can help businesses become more human-centric and transform the way traditionally labour-intensive industries operate, while simultaneously skyrocketing quality and efficiency and ensuring a robust supply chain.

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