Brual Shah

I co-founded GrayMatter Robotics with the mission to develop and deploy smart robotic systems by leveraging AI to assist humans in dull, dirty, and dangerous tasks. At GrayMatter Robotics our immediate focus is to develop Smart Assistants for Surface Treatment operations like sanding, polishing, buffing, grinding, deburring, spraying, etc. In the past, I have been a robotics researcher for over 9 years working on developing algorithms for realizing operations of robots in our daily life. Since 2012, I have been developing algorithms in the areas of motion and path planning, optimization, and machine learning. Until date, I have published 6 journal articles, 23 conference papers, and 3 patents. During my Ph.D., I have developed trajectory and path planners for unmanned surface vehicles (USVs) or unmanned boats that enable them to operate in environments of varying sizes and complexities. During my full-time employment at USC, I expanded my knowledge of decision-making algorithms and started implementing new algorithms for manipulator robots to enable advanced manufacturing applications. The algorithms I have developed are currently being used by robotic finishing (sanding, deburring, polishing, etc.), robotic 3D printing, robotic composite prepreg sheet layup, and assembly. Apart from academic research, I have been working with industry partners like Lockheed Martin, United Technologies Research Center (UTRC), Boeing, and Indiana Technology and Manufacturing Companies (ITAMCO) in adapting the developed algorithms and testing them on the business cases for robotic finishing, and composite layup applications. These projects are focused on TRL5 -TRL7 level development. I was part of the USC team that participated in the KUKA Innovation Award competition in 2017, where our team was one of the top five finalists and the only team from the USA. As a part of this competition, we presented a robotic finishing application in the Hannover Messe trade fair in Germany. I also participated in Agile Robotics for Industrial Automation Competition (ARIAC) organized by NIST in 2017 where our team was ranked first out of 50 teams. In this competition, we developed a kitting algorithm to efficiently assemble kits after the order is received and deliver them upon completion.