The days of clunky robotic arms struggling to manipulate objects are gone. Smart robotic grippers, powered by artificial intelligence, are revolutionizing the field of automation and robotics. The need for these intelligent grippers is increasing as we seek to optimize manufacturing processes, increase productivity, and improve efficiency across industries. These grippers possess dexterity, adaptability, and intelligence that enable them to handle a wide range of objects with precision. They are equipped with advanced sensors, sophisticated algorithms, and ingenious designs that mimic the finesse of the human hand, allowing them to interact with the physical world remarkably. One of the most exciting achievements in the field of robots with human intelligence is the development of a cognitive robotic gripper (COGBOT) employed for cognitive decision-making operations. Developed in Professor Dipti Gupta’s Plastic Electronics and Energy Laboratory (PEEL) group of the Metallurgical Engineering and Material Science (MEMS) department, Indian Institute of Technology, Bombay, India (IITB, India) the COGBOT is a 3D printed robotic gripper with two end arm tools designed for simple and lightweight tasks such as cleaning, cooking, targeted object delivery and transfer of objects over short distances for domestic and household purposes. The COGBOT not only have the ability to adapt to diverse shapes, sizes, and textures, for convenient, effective and stable gripping but can also ensure slippage-free and deformation-free gripping of the object, thereby overcoming challenges that have plagued traditional automation systems for decades.
The COGBOT operates on two servo motors- one connected to the pair of gripper arms through a spur gear arrangement and the other controls the alignment of the end arm-tool arrangement and is capable of rotation about their central axis for convenient gripping of the object. The end arm tools of the COGBOT are integrated with two identical capacitive-type proximity -cum- pressure sensors arrays. Lead researcher, Dr. Tania Mukherjee, expressed that these graphene-printed multi-sensor arrays (CAPSENSAR) bestow a human cognitive approach to the COGBOT during pick and drop and other manipulative operations. The flexible CAPSENSAR serves as an (8x8) proximity and pressure sensor arrays where the proximity sensor array, generates a contactless-capacitive impression of the object to construct the proportion-sized three-dimensional landscape of the different faces of the object. The algorithm determines the fittest pair of flattest opposite faces of the given object before the end arm tool aligns itself for cognitive gripping. The pressure sensor array generates the capacitive impression of the gripped object face at the computationally determined optimum gripping pressure and helps to prevent slippage. With built-in iterative close computational coordination between the CAPSENSAR and the microprocessor, the COGBOT can suitably align to the target object, grip at convenient faces and also routinely takes cognizance during slippage. The CAPSENSAR utilizes customizable electrode design, cost-effective and biocompatible materials, easy fabrication technique, making it commercially viable for rapid production and cost-effective manufacturing for use in COGBOT. The unique capabilities of the CAPSENSAR together with a simple algorithm can generate optimal grasping strategies for different objects and scenarios, as well as adapt to changing conditions and unexpected events. The operation of the COGBOT utilizes simple electronic circuits that are easy to fabricate thereby making it commercially viable yet futuristic and suitable for household acceptability. The estimated power consumption is only 3W and is powered by an Arduino Mega microprocessor board. According to Dr. Mukherjee, the COGBOT is a custom-printed robotic gripper, designed with human cognitive adaptability and aims to diversify robotic applications in lightweight tasks in households, and workplaces as well as in medical settings. The researchers tested their gripper on various tasks, such as picking up fruits and vegetables from a grocery store shelf, assembling Lego bricks into different shapes, and playing Jenga with wooden blocks. The results were impressive: the gripper was able to grasp and manipulate all kinds of objects with high accuracy and dexterity. It has many potential applications in real life. For example, it could be used in the household kitchen to handle delicate or irregular products that require human-like touch. They can pick up and move objects, sort items, and put things away, reducing the burden on homeowners and freeing up their time for more important activities. It can be a good companion for the old and the aged persons to assist them in their household chores and even the working couples to help them in their daily routine. Such grippers could handle various aspects of cooking and meal preparation, including chopping vegetables, stirring ingredients, and transferring items between surfaces. This could be particularly useful for busy individuals who want to enjoy home-cooked meals without spending excessive time in the kitchen. It could perform maintenance tasks like changing light bulbs, tightening screws, and handling minor repairs around the house. With the rise of online shopping, these grippers could help in receiving and handling packages. It could be used in hospitals to assist patients with disabilities or injuries. It could be designed to handle delicate objects, allowing for a more precise arrangement of decorations, artwork, and other items around the house. The possibilities are endless!
The researchers have recently published this work in the Communications Engineering journal. The full paper may be accessed through the link provided: https://doi.org/10.1038/s44172-023-00095-y. This work was patented under the Indian Patent Office, [Cite as T. Mukherjee, D. Gupta, A. Kushwaha (2021), “A robotic gripper for safe and cognitive gripping”, Granted by GOVT. of India (THE PATENT OFFICE) Patent No. 422349, Application No. 202121058266, Date of application 14.12.2021, Grant date 20.02.2023, Patentee- Indian Institute of Technology, Bombay]
Written by: Dr. Tania Mukherjee
Graphics design: Ambarish Paul
Cite the publication as: Mukherjee, T., Gupta, D. Cognitive gripping with flexible graphene printed multi-sensor array. Commun Eng 2, 57 (2023).