Term

Research

Other

Sem 1 (Aug-Dec)

E1241 (3)

(Core)

CP220 (3) (Core)

CP214 (3:1) (Core)

 Soft Core (3)

Optional

Sem 2 (Jan-Apr)

CP230 (2:1) (Core)

Soft Core (3)

Soft Core (3)

Soft Core (3)

CP210 (0:1)Core

Assignment of Thesis Project Advisor

Summer (May-Jun)

CP282 (1:2)(Soft Core)

Thesis Project (3)

Sem 3 (Aug-Dec)

Soft Core/Elective (3)

Soft Core/Elective(3)

Thesis Project (8)

Placement Interviews

Sem 4 (Jan-Apr)

Soft Core/Elective (3)

Thesis Project (15)

Course No

Course Name

Course Contents in Brief

Credits

Instructor

Semester

E1241

Dynamics of Linear Systems

State space modeling, Linear Systems, Linear Control

3:0

Vaibhav Katewa

Aug-Dec

CP 220

Mathematical Techniques

Intro to Probability, Linear Algebra, Bayesian Inference, Introduction to Optimization

3:0

Bharadwaj Amrutur

Aug-Dec

CP230

Autonomous Navigation & Planning

Navigation and planning for autonomous robots

2:1

Debasish Ghose/Mukunda

Jan-Apr

CP214

Foundations of Robotics

Modelling and simulation of robots

3:1

Shishir NY

Aug-Dec

CP210

Seminar

Exposure to latest topics in research and industry

0:1

Ashitava Ghosal

Jan-Apr

Course No

Course Name

Course Content

Credits

Faculty

Semester

AE372

Applied Optimal Control and State Estimation

Calculus of Variations & optimal control formulation, Two-point boundary value problems, LQR, STM, SDRE, HJB theory, MPSP design & extension etc

3:0

Radhakant Padhi

Jan-Apr

E1242

Nonlinear Systems and Control

Consensus over networks with applications in synchronization & opinion dynamics, stabilization over rate limited & quantization channels, Network protocol design, Decentralized optimal control & information patterns, security & privacy in networked control systems

Pavan T

Jan-Apr

E1246

Topics in Networked and Distributed Control

Relevant background topics in control, Estimation & control under communication constraints, event triggered control, connectivity maintenance, security in networked & distributed control systems, applications in robotics & transportation

Vaibhav L./Pavan T

Aug-Dec

E1277

Reinforcement Learning

MDP, Reinforcement Learning

3:1

Shalabh B/Gugan Thoppe

Jan – Apr

E0272

Formal Methods in Computer Science

Model checking, program verification

3:0

Deepak D.

E3258

Design for IoT

Introduction to IoT, Challenges in IoT – Power, Security, Identification, Location, Low Power Design, Energy harvesting systems, Power management algorithms, ARM processor low power features, multiprocessor systems, Lifetime estimation, RFID and its applications, backscattering techniques, Working with protocols such as MQTT, COAP, for low power and energy harvesting sensor nodes, Low power wireless networks – Bluetooth Low Energy (BLE), and IEEE 802.15.4e TSCH.  Low Power Wide Area Networks – LORA, NBIoT and power-saving modes, CAT-LTE-M1.

2:1

T V Prabhakar

Aug-Dec

CP312

Design of CPS -II

C/C++, Realtime OS, Embedded Programming

2:1

Darshak Vasavada/Ashish Joglekar

Jan-Apr

Replaced by another course CP 316-Real time embedded systems

CP212

Design of CPS-I

This is an interdisciplinary course on the design of cyber-physical systems, inviting students from all the departments. It provides an in-depth exposure to various elements of a CPS: the microprocessor, memory and IO devices. The course also includes interfacing sensors and actuators and implementing a control loop.  This course uses a practical approach and involves significant C programming on embedded hardware.

2:1

Bharadwaj Amrutur/ Darshak Vasavada

Aug-Dec

CP232

Swarm Robotic System

Autonomous operation of Drone/Robots, Swarm Intelligence (Self-Organization & emergence). Motion control, planning, target tracking, predator-prey, formation, Cooperation and Coordination, Market, team theory, game theoretic approaches, decision making under uncertainty

2:1

Suresh Sundaram/Jishnu Keshavan

Jan – Apr

Changed to Aug-Dec

PD232

Human-Computer Interactions

Basic psychology of Perception and Motor Action, Collaborative Robots, Introduction to AR/VR and Haptics systems, Facial Expression Recognition, Case studies on HRI

2:1

Pradipta Biswas

Aug-Dec

CP 314

Robot Learning and Control

Machine learning based control for robotic systems

3:1

Shishir NY

Jan-Apr

This one to be retained for sake of old students

CP 315

Robot Learning and Control

Machine learning based control for robotic systems

2:1

Shishir NY

Jan-Apr

New one with reduced credits

CP260

Perception & Intelligence

Localization & Mapping, Multi-Sensor Perception, Knowledge Representation, Reasoning

2:1

Bharadwaj Amrutur/Raghu K

Jan-Apr

 CP216

Industrial IoT systems

Industrial protocols such as Time Triggered Ethernet, Time Sensitive Networks, Detnets, Modbus/TCP, PLC systems, Construction of Digital twins, Condition monitoring,

2:1

TV Prabhakar

Jan-Apr

CP242

Human Robot Interactions

Introduction; Cross-disciplinary foundation; Hardware and Software components and architecture; Research themes; Building blocks; Navigation, Interaction, Manipulation, and Behavioral aspects for Social Robots; AI for social robots (including Autonomy and Learning for Social Intelligence); Designing a social robot (including Humanoid, mobile and interactive robots); User Studies; Pointers to advanced Topics in the domain.

2:1

Pradipta Biswas/Amit Pandey/Sridatta Chatterjee

Jan-Apr

CP274

Formal Analysis and Control of Autonomous Systems

This course will provide an end-to-end overview of different topics involved in designing or analyzing autonomous systems. It begins with different formal modeling frameworks used for autonomous systems including state-space representations (difference equations), hybrid automata, and in general labeled transition systems. It also discusses different ways of formally modeling properties of interest for such systems such as stability, invariance, reachability, and temporal logic properties.

As a next step, the course will cover different techniques on the verification of such systems including Lyapunov functions, reachability, barrier certificates, and potentially model checking. Finally, the course will introduce students to several techniques for designing controllers enforcing properties of interest over autonomous systems.

3:0

Pushpak Jagtap

Jan-Apr

CP316

Real-time Embedded Systems

The course is organized in three parts: standalone (OS less) systems, multi-tasking systems with RTOS and systems with embedded OS. The course involves significant programming in C on embedded platforms running RTOS / embedded Linux.

Part 1: Standalone systems: 4 weeks

Software architecture: control loop, polling and interrupt driven systems, PID control and finite state machine

Experiments: interfacing sensors and actuators to implement a standalone control system on an ARM based hardware platform.

Part 2: Multi-tasking systems: 6 weeks

Introduction to real-time systems, multitasking, scheduling, inter-task communication, memory management and device drivers

Experiments: build a multitasking system involving multiple simultaneous activities involving computing algorithms, IO processing and a user interface.

Part 3: Embedded Linux: 4 weeks

Building an embedded Linux system; processes and threads, memory management, file-system, drivers. Real-time limitations and extensions.

Experiments: build connected application with sensor/actuator front-end and embedded Linux for UI and connectivity.

2:1

Pushpak Jagtap/Darshak Vasavada

Jan-Apr

CP218

Theory & Applications of Bayesian Learning

Descriptive Statistics, Introduction to Probabilities, Bayes Rules, Probability Distributions, Maximum Likelihood Estimation, Bayesian Regression and Classification, Expectation Maximization, Frequentist vs Bayesian Learning, Conjugate Priors, Graph Concepts, Bayesian Belief Networks, Probabilistic Graphical Models (PGMs), Probabilistic and Statistical Inferencing, Bayesian Estimation, Structure Learning, Bayesian Optimization, Markov Random Fields, Markov Chain Monte Carlo, PGM examples and applications (including industry and smart cities applications)

2:1

Punit Rathore

Jan-Apr

CP318

Data Science for Smart City Applications

Data types (spatio-temporal data, event data, trajectories, time-series, point-reference etc.), data pre-processing (filtering, discretization, standardization, transformation, Imputation etc.),  Regression (linear regression, passion regression), spatio-temporal estimation (kriging, Gaussian process regression etc.), data dissimilarity measures, Pattern discovery (frequent pattern mining, clustering (event, time-series, trajectory clustering, spatio-temporal clustering etc.), Classification (logistic regression, Bayesian classification, SVM, Ensembles), Anomaly/Outlier Detection Techniques, Concepts for big data mining and visualizations (sampling techniques, dimension reduction (PCA, Manifold learning, Self-organizing maps etc.)), Concepts for stream data mining, MapReduce framework.Throughout the course, students will learn to use real data to solve smart city application problems via data science techniques covered in this course.

2:1

Punit Rathore

Aug-Dec

CP280

Experimental Techniques for Robotics& automation

ROS/ROS2, SLAM, Networking, Navigation, Planning, Competition Project

1:2

Bharadwaj Amrutur/Ashish Joglekar/Naveen Arulselvan/Kaushik Sampath

Jan-Apr/Aug-Dec

Changed from core to soft core

CP282

Field Robotics

Competition Style, Team Based Robotics Project

1:2

Bharadwaj Amrutur/Suresh Sundaram/Pushpak Jagtap

Aug-Dec/ Summer(May-Jun)

E1244

Detection & Estimation Theory

3:0

Vaibhav Katewa

Jan-Apr

NE250

Entrepreneurship

Entrepreneurship, Ethics & Societal Impact

1:0

Madhu Atre

TBD

Name

Contents

Mobile Robot Programming

Learn to program mobile robots to navigate around an obstacle course

Control of Industrial Robot Arms

Learn to program industrial robot arms to do various tasks like pick and place, movements, gripping, welding etc. Program collaborative arms.

Programming of Drone Systems

Program drones for landing, sorties, pattern flying, etc.

Tele robotics

Control robot arms/humanoids over the network.

Robot simulation frameworks

Exercises in Simulation frameworks like PyBullet, Gazebo by creating robot and world models, demonstration of various algorithms

VR/AR & Speech Interfaces

Programming VR/AR, haptics and speech interfaces to machines/robots

Human Robot Interaction

Interfacing Robots with interactive devices like gesture and speech recognition systems, eye gaze tracker, Industrial CoBoT, TeleRobotics, HRI for semi-autonomous vehicle, cognitive load estimation (“human/operator state” might be a broader term?)

ROS/ROS2 Software Stacks

Robot programming using ROS/ROS2

Machine Learning for Robots

ML based Control for Grasping and Manipulation

Robot Sensor and Actuator Systems

Integrate new sensor and actuator system to a robot’s perception system

3D Design and Prototyping for Robotics

3D CAD design, URDF model creation, 3D printing of part and attachment to a robot

Drone piloting

Learn to fly drones in IISc testbed

Multi-sensor odometry

Wheel, IMU, GPS, Lidar, wireless, and combinations by filter-based fusion

Visual navigation

Tag-based, landmark-based, feature based, direct methods, deep learning based, monocular and stereo methods