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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. Final Application Deadline - Sept 09, 2021
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8 Semester Curriculum The curriculum at Plaksha is dynamic and continuously evolving, based on inputs from faculty, latest research and industry insights.
  • Semester 1
  • Semester 2
  • Semester 3
  • Semester 4
  • Semester 5
  • Semester 6
  • Semester 7
  • Semester 8
Innovation Lab & Grand Challenge Studio I

This course, referred to as ILGC, introduces the Grand Challenges at the interface of societal needs and technological capabilities. It will offer the opportunity for students to develop an interdisciplinary appreciation for engineering from a technical perspective as well as from a global and historical perspective. Students will embark on this integrated, project-based journey in the 1st semester and work on different projects throughout the four-year program. First semester topics include - Exposure to different Grand Challenges and project areas, design cycle, grand challenge thinking, geopolitics and global awareness, and entrepreneurial mindset.


Critical Thinking & Scientific Reasoning

What are the assumptions and beliefs that we have not examined in the modern age? How do we become aware of our implicit beliefs? What possibilities open up if we investigate and examine our presuppositions? How can we respond to the Grand Challenges of our time, if we don’t know how to think and reason critically? In this course, you will learn to meticulously develop the skill of thinking and enquiring critically, and being able to reason in a scientific, evidence-based manner. The course will focus on sharpening your intellectual abilities so that thinking critically and scientifically becomes a natural way of approaching the world. You will learn how to carefully analyze texts, structure arguments, develop technical reading and writing skills, and communicate your ideas in a coherent and logical manner to different audiences. Additionally, you will also learn to evaluate hypotheses and causal claims, observe and analyze data and patterns, construct reason-based arguments, and draw logical conclusions.


Engineering Mathematics in Action

In this course, students will be introduced to foundational aspects of engineering mathematics, specifically linear algebra, matrices, and ordinary differential equations. The course is divided into four modules, two modules each on linear algebra and ordinary differential equations. The topics included under the linear algebra modules are definition of vector spaces, concepts on linear independence of vectors, bases, rank of a matrix, solutions to linear systems, definition and interpretation of eigenvalue problems, and singular value decomposition and their applications. The topics under ordinary differential equations are methods to solve simple linear differential equations using both analytical (method of undetermined coefficients, variation of parameters) and numerical techniques (Runge-Kutta methods), basics of phase plane analysis, stability of solutions based on eigenvalue analysis, fixed points, and elementary concepts on bifurcation and chaos. Each module will comprise a computer-based laboratory project.


Fundamentals of Computational Thinking

This course provides students with an understanding of the role that computational thinking can play in solving problems. Students will be exposed to varied real-world problems and be taught how to approach them and design solutions using Python. In addition to learning key computing skills and concepts, the course will focus on how existing features in programming languages can be used to implement different concepts efficiently and how one can analyze different solutions. After taking the course students are expected to work on real-world projects that require building logical thinking processes that break down complex problems into smaller parts.


Foundations of Physical World

In this course, students will be introduced to classical mechanics, quantum mechanics, statistical mechanics, and connections to engineering thermodynamics. Molecular origin of macroscopic descriptions and constitutive relations for equilibrium and non-equilibrium behavior; fluctuations, kinetics, and limitations of macroscopic descriptions. Macroscale continuum origin of lumped models: ‘through’ and ‘across’ variables for analysis of electrical, mechanical, structural, thermal, acoustic, and fluidic systems.


Design Thinking

This course introduces students to harness the power of design thinking to develop innovative solutions to complex human-centered problems. The design thinking methodology will help students learn about the underlying context and the innovation need, brainstorming and developing prototypes, testing potential solutions, improving them, and developing new insights. Students will be exposed to core technology and design themes including principles, modes of thinking and analysis, and social and cultural aspects of design. They will learn how to use the ideation process to generate new ideas and select promising solutions, use prototyping tools to visualize and communicate ideas and develop the implementation plan for an effective solution.


Innovation Lab & Grand Challenge Studio II

Building on the ILGC journey from Semester 1, ILGC II will introduce students to starting their team projects, implementing principles of Design Thinking, embarking on a campus-wide project, and interacting with real-world stakeholders. Students will also learn how to work with various tools and build skills in machining, programming, instrumentation, among others.


Reimagining Technology & Society

In this course, we will rigorously enquire into the different meanings of the idea of technology and its relationship to society from the perspectives of philosophy, history, social anthropology, human evolution, and civilizational studies. We will look at examples from the past and present, but more importantly, also start imagining what the relationship between technology and society could be in the future. We will ask a number of questions pertinent to this inquiry: Does technology influence society, or, does society influence technology? What indeed is technology? Is technology perhaps first and foremost an ‘idea’? Or, is technology a particular way of knowing the world around us? If it is an idea then it must involve thinking of some kind. But clearly it also involves making something – usually an object that does something or has a particular function. In this course we will begin to understand technology from the standpoint of the threefold matrix of thinking, knowing, and making.


Mathematics of Uncertainty

This is an introductory level UG course on probability and statistics. Topics include conceptual introduction to probability axioms, conditional probability, Bayes' theorem, law of total probability and expectation, measures on central tendency and dispersion, probability distributions, simple discrete and continuous probability distribution models, elementary concepts on discrete and continuous time Markov processes, least squares regression analysis, sampling distributions and elementary ideas on hypothesis tests. Students will have to complete an end-of-term project on a topic of their choice.


Programming & Data Structures

Building on the Python course taught in the previous semester, students will be introduced to the Object Oriented Programming (OOP) paradigm and the associated benefits. They will learn to write structured and efficient programs in the OOP style. Besides testing and debugging programs, students will learn about common data structures, and where and how to apply them to solve computational problems.


Nature’s Machines

This course introduces students to how nature’s machines work. It covers various aspects that relate the design of living matter/things to engineering. We will discover how to think about: a) the human cell as a factory, the circulatory system as a transport network, musco-skeletal system as a structural network for load-bearing, magnetoreception in animals as a communication system, among other topics. b) Aspects of biomedicine such as the design of impedimetric sensors, digital health, and tissue and genetic engineering. c) Diversity and dynamics of nature pertinent to engineering through several demo examples and recent state-of-the-art applications.


Fundamentals of Microeconomics

The course introduces core microeconomic models of consumers, firms, and markets, and develops their application to a broad range of economic and social issues in the real world. It will cover concepts of equilibrium, markets and competition, market demand and market supply, behavior of consumers and producers, consumer and producer theory, pricing, tax incidence, making choices under uncertainty, economic efficiency, etc., in the context of contemporary real-world applications around us such as Uber surge pricing, telecom price wars, e-commerce models, recent ed-tech acquisitions, etc.


Innovation Lab & Grand Challenge Studio III

In this course, students continue to build on their IL/GC projects, with an eye for expansion at the city level. They will be able to develop multidisciplinary approaches and interdisciplinary perspectives by interacting with and making connections between disciplines; analyzing the humanistic, social, historical, economic, and technical contexts of problems. In addition, they will continue to iterate their designs and work on skills such as developing innovation and entrepreneurial mindset, becoming a better communicator and leader, and understanding the social and human consequences of actions and responsibilities to others in local, national, and global communities.


The Ethics of Technological Innovation

The advent of technology since the turn of the century has led to many advancements in the way that humans live and operate. This progress, however, also comes with apprehensions, uncertainty, and questions regarding the ethical considerations associated with the owners, regulators, and users of the technology. In this course, we will examine the manifold ethical issues surrounding the use and development of AI, Robotics, Biology, and Business based technologies in the contemporary world. Students will be introduced to ideas of safety, privacy, regulations, and related consequences of bias, manipulation, and fairness, from a multidisciplinary perspective. Students will be introduced to ideas from traditional philosophical ethics texts before delving into real world case studies focussing on contemporary issues.


Mathematics for Continuous Systems

This course will introduce foundational ideas on mathematical transforms like Laplace and Fourier transforms. Additionally, there will be a two month long module on partial differential equations and vector calculus. In addition to lectures, students will participate in a semester long, state of the art physical laboratory immersion program which will involve training and tinkering with experimental mathematics, such as profiling heat conduction through a metallic rod to understand the mechanics of the heat equation and its solutions, performing fluid mechanics experiments using a rotating tank of water and high-speed camera to collect data and understand the solution states of the Navier Stokes equation, using wavemaker and wave guides to calculate wave velocity and comparing the data with theoretical calculations, performing laboratory experiments with spectrometers to estimate power spectral density of signals and compare the results with mathematical calculations in Fourier space, etc.


Data Science & Artificial Intelligence

This course offers an introduction to the areas of Data Science, Artificial Intelligence, and Machine Learning (DS/AI/ML), combining philosophical, biological, and psychological perspectives with computational design concerns. Students will begin the course by understanding the principles underlying learning and how it translates to various applications and categories of AI. Besides multiple classes of models, students will be introduced to fundamental concepts in data science that will help them identify, compare and implement solutions to problems. Internal critiques and external perspectives of AI solutions will also be discussed to ensure students obtain a holistic view of the challenges and opportunities in this field.


Intelligent Machines

This course introduces the students to the idea of intelligence and how intelligent machines are transforming the world around us. Students will learn about the concept of cyber-physical systems and how intelligence stems from the ‘perception, reasoning, and action loop’. Students will explore several examples of cyber-physical systems in the real world in areas such as robotics, smart grids, and autonomous cars. They will learn about mathematical techniques for modeling cyber-physical systems, how to build intelligent machines by combining sensors, actuators, and embedded devices. Through hands-on lab activities, assignments, projects, as well as through guest lectures spanning research and practice, students will be able to gain the skills to design, build and evaluate simple cyber-physical systems that will give them the confidence to pursue more complex projects in their future endeavors.


Foundations of Optimization

This course offers a multidisciplinary overview of the field of optimization. Students will learn how to formulate an optimization problem, apply different optimization techniques, translate problems into Python and Matlab code, and identify conditions under which each one works best. Students will be introduced to numerical, constrained, unconstrained, univariate and multivariate optimization methods and techniques, while also being introduced to topics such as Pareto optimality, multiobjective and global optimization. The final project will allow students to apply their knowledge to real-world engineering and business problems.


Innovation Lab & Grand Challenge Studio IV

In Semester 4 students will decide the IL/GC project (coincides with choosing their major) and team they will be part of, and initiate the first steps of the project that will culminate with their capstone. Projects chosen by students will be connected and coherent in design, looping in a wide range of technology such as sensors, IoT, automation, robots, AI/ML, data science, biosystems design, etc. The core focus would be on implementing the engineering design cycle and reflecting on progress, to create solutions implementable at a city level, with an eye for expansion at state level. Mentored Leadership and Professional Development opportunities will be a constant feature across the 4 year IL/GC 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.


Signal & Systems

The subject presents an overview of the key mathematical concepts applied in the field of signal processing and shows how abstract concepts like complex numbers, convolution and mathematical transforms are used in devices like wireless systems for signal filtering and image enhancement. The subject will expose students to engineering projects like designing an advance filter system for mobile phone receivers and image processing algorithms.


System Dynamics & Control I

The students will be exposed to basic concepts of control systems and how control systems are utilized in everyday life. The students will learn the concept of feedback and how open and closed loop systems work. They will also learn how to model and represent physical systems using differential equations and use the simplified system model for controller design. The students will learn to analyze linear time invariant systems using time domain and frequency domain techniques and will learn to design PID controllers. These concepts will be implemented by students in the lab so that they can appreciate the complexity involved in controlling real-world systems. The students will be evaluated both on their ability to master the theoretical concepts and to implement these concepts on simple physical systems in the laboratory.


Mechanics & Mechanisms

The students will be first exposed to basics of mechanics and materials selection in engineering design of machines. The next module will cover the analysis of mechanisms and machine elements which form the backbone of any robotic system. Finally, the most important aspect of this course will be a group project encompassing design, modelling and analysis, synthesis, fabrication of a complete system/product based on the knowledge acquired in the course.


Analog & Digital Electronics

The subject presents a broad overview of hardware aspect of electronic devices and how they operate in a synergistic manner while using analog and digital components. The topics would cover the design of devices like rectifiers, audio amplifiers, radio receiving sets & mobile phone front end circuits.


Application Domain Track I

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 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 IL/GC 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

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 IL/GC 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.


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

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.


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


Learning Experiences

Experiential Learning

Integrated learning experience across 4 years. Students work on authentic, real world projects through industry and community.
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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.
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The core curriculum will not just be limited to engineering and sciences, but bring in exposure to entrepreneurship and design which will enable humane and empathetic outcomes through technology. Each student will undertake multiple different experiences to develop skills like finding opportunities, creating value, and embracing risks. Students will be mentored and supported by Plaksha founders and professionals from industry.
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At Plaksha, learning and skill development do not stop in the classroom. Students will have the opportunity to create and immerse themselves in pursuing their academic and creative interests. Student led clubs will be autonomous bodies that operate under the purview of the Office of Student Life. Being the founding batch, students will be encouraged to help establish a vibrant culture through clubs and societies on campus.

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.
Find the answers to your questions in some of our frequently asked questions by students

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