UG Program | 4 years

B.Tech in Robotics & Cyber-Physical Systems

Solutions to grand challenges increasingly require reaching across the boundaries of the cyber, physical & human worlds. The Robotics & Cyber-Physical Systems program is different from traditional electrical & mechanical engineering programs & is designed to target the growing & unmet need at the intersection of computing, mechatronics, & human behavior. Students will be able to design engineering systems that interact with humans & environment & create solutions to tackle some of India’s & the world’s most pressing grand challenges.

8 Semester Curriculum The curriculum at Plaksha is dynamic and continuously evolving, based on inputs from faculty, latest research and industry insights. B.Tech in Robotics & Cyber-Physical Systems syllabus outline is given below.

Semester 1
Semester 2
Semester 3
Semester 4
Semester 5
Semester 6
Semester 7
Semester 8

Computational Thinking

Instructor(s) - Dr. K Gopinath, Dr. Manoj Kannan

Coding Café (Python & LINUX)

Instructor(s) - Dr.Srinivasan Vishwanathan

Engineering Math in Action

Instructor(s) - Dr. Amrik Sen, Dr. Saikat Chakraborty

Engines of Life

Instructor(s) - Dr. Monika Sharma, Dr. Manoj Kannan

Environmental Science

Instructor(s) - Dr. Prashanth Suresh Kumar

The Art of Thinking and Reasoning

Instructor(s) - Dr. Aditya Malik, Dr. Brainerd Prince

Universal Human Values

Communication Lab

Instructor(s) - Dr. Brainerd Prince

ILGC: Design and Innovation

Instructor(s) - Dr. Amit Sheth, Dr. Rucha Joshi

Innovation Lab & Grand Challenge Studio V

Continuing their project progress from semester 4, the goal for Semester 5 and 6 will be to implement solutions via projects at the State level, with an eye for expansion at the National level. To achieve this, students will seek validation of concept from various stakeholders, complete the engineering design cycle of their project, while also developing an entrepreneurial spirit from their experiences. Mentored Leadership and Professional Development opportunities will be a constant feature across the 4 year ILGC experience, and will be integrated with project work. These serve to develop the student’s professional skills and also help in creating a more integrated socio-integrated understanding of engineering/design.

Embedded System Implementation

Embedded systems form the heart of industrial electronics of contemporary times. The subject will be focused on development of practical devices and systems which drive and control consumer devices ranging from microwave ovens, washing machines to drones and automatic vehicles.

Robotic Systems I - Sensors & Actuators

The students will be introduced to common sensors and actuators utilized in mobile robots and manipulators. This will be a “hands-on” project based course where the students will learn the fundamentals of sensors and actuators and will learn to use these sensors and actuators on a mobile robot. Fundamentals of force and torque sensing will be introduced. Simple pose estimation using a vision system will be introduced. The students will learn to represent sensor information in different coordinate systems. Actuators will cover the concept of different types of motors, motion transmission devices such as gears and linear actuators.

Technical Elective I

Sample Electives include: Manufacturing and Automation, Fluids in Action, Autonomous Systems, Systems Engineering, Distributed Computing and Connected Systems, Swarm Robotics

Free Elective I

Students may take courses from other majors as part of the free elective. Additionally, faculty may also offer some introductory electives as part of this sequence.

Application Domain Track II

The Application Domain Tracks are a series of 1 credit modules that help students inculcate skills and mindsets related to research and entrepreneurship. Through these tracks, students will contribute to ongoing research projects in Plaksha's flagship grand challenge research centers, and may work with faculty on their research or on approved external projects in industry/government or startups. Across semesters, students will have the option to work across different disciplinary areas or focus on one area but the purpose is for them to appreciate the relevance of their coursework to a variety of challenges and areas.

Innovation Lab & Grand Challenge Studio VI

Networks & Protocols

Considering the layered network structure of modern networks, this course takes a top-down approach starting from the Application Layer and then continuing on to the underlying Transport, Network, Data Link and Media Access Control (MAC) Layers. Network Applications are illustrated as software running on the end-hosts which use the underlying end-to-end Transport Layer to transact transport layer segments as required by the applications. The Transport Layers of the end-hosts similarly use the underlying Network Layer to transport datagrams to each other where these may be routed appropriately through intermediate nodes of the network. These in turn use the underlying Data Link and MAC layers to transport data packets from one host to the next with appropriate network routing to allow the network layer datagrams to find their own way across the network, from the source to one (unicast) or more (multicast) destination(s). Though the IEEE802.3 ETHERNET is described briefly, the course places special emphasis on the 802.11 WiFI network which is ubiquitous today. The structure and approach of these networks are discussed in detail. The basic aspects of network security is also discussed. The lecture material will be supplemented with analytical assignments to be done at home and programming assignments to be done in the Computer Lab.

Robotic Systems II - Manipulation

The students will be introduced to the fundamentals of grasping and manipulation. The course will cover topics such as forward and inverse kinematics, dynamic modeling of robotic manipulators using simulations, trajectory and path generation. Configuration space trajectory and operational space trajectory generation. Control of robotic manipulators in joint space and task space. The students will apply these concepts in a lab in a simulation environment and will also learn to program the motion of a 6-axis robot.

Technical Elective II

Sample Electives include: Manufacturing and Automation, Fluids in Action, Autonomous Systems, Systems Engineering, Distributed Computing and Connected Systems, Swarm Robotics

Free Elective II

Students may take courses from other majors as part of the free elective. Additionally, faculty may also offer some introductory electives as part of this sequence.

Application Domain Track III

Advanced Network Architectures

The Internet of Things (IoT) is envisaged as a network of diverse objects embedded with sensors, and appropriate hardware and software to connect to and exchange data with other similar devices or with the broader Internet for supporting shared applications. Though one tends to think of IoT mostly for home and industrial automation, it is expected to become prevalent in Smart Cities, Smart Grids and Smart Farming applications. Building on traditional networking approaches using TCP/IP, the IPv6 protocol is presented as the network layer of choice for IoT. Moving on from classical IEEE 802.11 WiFi, the data link layer based on the IEEE 802.15 standards will be discussed. Specifically, the course will describe Bluetooth, High-rate and Low-rate WPANs (Zigbee) and Mesh Networking with special focus on infrastructure-less networking as in Adhoc Networks and Mobile Adhoc Networks (MANETs). The course will close with some discussion of Cloud Networking and Content Distribution Networks (CDNs) The lecture material will be supplemented with analytical assignments to be done at home and programming assignments to be done in the Computer Lab.

Systems Dynamics & Control II

This course introduces the students to the concepts of state space methods for feedback control design and state estimation. The examples will be drawn from a variety of problems related to robotics and cyber-physical systems. The course will be divided into two modules. In the first module, the students will learn the fundamentals of state space methods, equivalence between transfer functions and state space representations, concept of controllability and observability, pole placement method for controller design. The second module will introduce basic ideas of state estimation and will include concepts such as Observability, Luenberger observer and Kalman filters. The students will implement the concepts in simulation and real life applications during lab sessions.

Technical Elective III

Sample Electives include: Manufacturing and Automation, Fluids in Action, Autonomous Systems, Systems Engineering, Distributed Computing and Connected Systems, Swarm Robotics

Humanities & Social Science Elective I

Sample electives include: AI for Social Good, Technology, Policy and Law, Decision Making Under Uncertainty, Fairness, Transparency, Accountability, and Ethics in Data Science

Innovation Lab & Grand Challenge Studio Capstone

ILGC transforms and culminates as a two semester capstone design project. By the end of the seventh semester a detailed design of the final product (this could be a device, system, process, software, etc. that results from this design experience) needs to be completed. This includes but not limited to the following: Description of the overall project, including a description of the customer and their requirements, the purpose, specifications, and a summary of the approach. Description of the different design approaches considered and evaluation of each design approach. Detailed description of the final proposed design.

Smart Networks

In this course, students will learn how the advent of IoT, sensors and automation has led to the development of smart networks. The course will cover several examples of complex cyber-physical networks in different domains such as smart grids, transportation/logistics networks and the internet and will explore how the advent of IoT technologies has transformed each domain. The students will learn to analyze the properties of these sensor networks and will explore opportunities for optimization of resources. As project work, students will be encouraged to apply the skills learnt to analyze real life problems in their community. Through this project they will also think about the challenges related to ethics, security and privacy related to smart networks.

Autonomy - Planning & Decision

This course will cover the fundamentals of perception, planning and decision making in robotics. The students will learn about robot localization and mapping concepts and will learn about various motion planning controls. Ideas of decision making under uncertainty will be introduced. Finally, ideas of multi-robot path planning will be introduced. Extensive use of the Robot Operating System (ROS) for demonstrations and hands-on activities. We will also examine case studies in ground and aerial robots, manipulators and multi-robot systems.

Technical Elective IV

Sample Electives include: Manufacturing and Automation, Fluids in Action, Autonomous Systems, Systems Engineering, Distributed Computing and Connected Systems, Swarm Robotics

Humanities & Social Science Elective II

Sample electives include: AI for Social Good, Technology, Policy and Law, Decision Making Under Uncertainty, Fairness, Transparency, Accountability, and Ethics in Data Science

Innovation Lab & Grand Challenge Studio Capstone

ILGC transforms and culminates as a two semester capstone design project. By the end of the eighth semester, students will have a working product (this could be a device, system, process, software, etc. that results from this design experience). Therefore, the focus of this semester is to implement, test and evaluate the design approach chosen in your first semester. The following are the expected requirements and deliverables for this semester: Working final product Testing and evaluation of product design Demo of the final product Completed Project Description, Final Reflection and Completed Outcomes Matrix

What can you create?

Autonomous Vehicles

You can create autonomous vehicles such as self-driving cars, that are capable of sensing their environment and can communicate with adjacent vehicles to avoid accidents, reduce traffic and ensure that no traffic rules are violated.

Digital agriculture solutions

You can create digital agriculture solutions that enable farmers to monitor aspects like irrigation, crop yield, environmental conditions, etc., through low-cost sensors, drones, and mobile communications and data across the agricultural value chain. By driving adoption of such solutions, you can enable farmers to boost sustainable farming practices and maximise return from their crop.

Smart cities

You can help conceptualize and build exciting “Smart Cities” of the future, which have smart interconnected systems for transportation, energy distribution, healthcare, environmental monitoring, emergency response and more, while preserving aspects of safety, security and privacy.

Medical robotics

You can design and develop wearable prostheses that adapt to a patient’s injuries and guide individualized exercises in conjunction with a remote therapist, build robots that perform meticulous and high-risk surgeries, real-time patient health monitoring and various other solutions that revolutionize healthcare.

Industrial and consumer robots

You can build robots to perform tasks that create economic value and simplify our lives, such as industrial robots used in manufacturing and logistics processes, to even robots that clean our homes!

Learning Experiences

Multidisciplinary approach & interdisciplinary perspective

Interacting with and drawing from multiple fields of expertise, making connections between disciplines, analyzing the humanistic, socio-economic, and technical contexts of problems.

Foundational Tech core

Developing an interdisciplinary foundation featuring math, physics, computer science and engineering principles such that they come together as an integrated whole, not segmented topics.

Design & research ability

Identifying and understanding human needs and solving problems creatively through sustained critical investigation.

Innovation & entrepreneurship mindset

Finding opportunities, identifying business models, embracing ambiguity to create value in the marketplace or in society.

Societal responsibility

Considering the social and human consequences of actions and responsibilities to others in local, national, and global communities; acting to improve the human condition.

Leadership & self-reflection

Creating impact through actively developing skills like communication, creativity, critical thinking and collaboration.

Experiential Learning

Integrated learning experience across 4 years. Students work on authentic, real world projects through industry and community.

Coding Cafe and Makerspaces
Entrepreneurship
Student led clubs

By having access to state-of-the-art makerspaces and coding cafes and incorporating them in the curriculum, students will become more context-aware, develop critical thinking abilities, and learn by creating. This will help foster a tinkering and problem solving mindset, immersing students in experiential learning from day one. These areas will be open to students to explore, create, prototype and design, while also housing equipment and technologies like 3D printers, sensors, etc.

Hear about the course from the experts

Watch Dr. Hanumant Singh of Northeastern University and Dr. Richard Voyles of Purdue University explain the relevance and scope of this B.Tech degree.