Arindam

Task allocation in a multi-robot system is required to determine which robots should execute which tasks, to achieve the overall system goals. Task allocation is an important aspect of many multi-robot systems, which ensures coordinated team behaviour. In this talk, we describe the features and complexity of multi-robot task allocation (MRTA) problems, which are determined by the requirements of the domain. We illustrate how to classify these problems in a systematic manner and show some real-life applications.

We show a very general formulation of the task allocation problem that generalizes several versions that are well-studied in the existing literature. Our formulation includes the states of robots, tasks, and the surrounding environment in which they operate. We describe how the problem can be varied depending on the feasibility constraints, objective functions, and the level of dynamically changing information. We illustrate an algorithm to solve a particular variant of the MRTA problem and show how this algorithm performs better than current state-of-the-art algorithms on real datasets. We conclude the talk with some directions for future research.

Biography:

I am the Chief Executive Officer, Director, and Founder of TechSoftX Corporation. TechSoftX is the next generation software company. We develop products, provide consulting, training, services, support, and partner with other companies to sell their products and services. Previously, I was a Director of Operations Research and Data Science at Optym, where we made transportation companies more profitable and efficient through the use of optimization and AI. Before that, I was a Senior Research Scientist at Data61 in Commonwealth Scientific and Industrial Research Organisation (CSIRO) and a Senior Research Fellow at Cyber Security Cooperative Research Centre (CSCRC). I am also a Conjoint Senior Lecturer at University of New South Wales. Previously, I was a Research Scientist at TCS Research and Innovation. I earned my Ph.D. in Theoretical Computer Science (TCS) from the Department of Computer Science and Engineering, Indian Institute of Technology Delhi. My Ph.D. research advisors were Professor Amit Kumar and Professor Naveen Garg.

My primary areas of expertise are Artificial Intelligence (AI) and Machine Learning (ML). This is the scientific study of algorithms and statistical models that computer systems use to perform a specific task, without using explicit instructions. My broad research interests are:

• Artificial Intelligence, Data Science and Machine Learning
• Analysis of Complex Networks and Social Networks
• Approximation, Randomized and Online Algorithms
• Combinatorial Optimization and Mathematical Programming
• Cyber Security

In my previous life, I worked as a Technical Lead at Yahoo! Research and Cognizant, and as a Software Design Engineer at Microsoft Corporation and Novell Inc. I also did internships at IBM Research and Yahoo! Labs. I completed my Master of Engineering from the Department of Computer Science and Automation, Indian Institute of Science Bangalore and Bachelor of Engineering from the Department of Computer Science and Engineering, Jadavpur University, Kolkata, both in Computer Science and Engineering. I had the privilege of working with Professor Samiran Chattopadhyay at Jadavpur University and Professor Ramesh Hariharan at IISc Bangalore, who is the Co-founder and Chief Executive Officer of Strand Life Sciences.

Email:

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