MTech RAS Curriculum 2023

MTech (Robotics & Autonomous Systems) Program Plan at a Glance 

 

Total number of credits: 64 (17 Core + 15 Soft Core + 6 Electives+ 26 Thesis Project) 

Suggested Template 

Term 

 

Research 

Other 

Sem 1 (Aug-Dec) 

E1241 (3) 

(Core) 

CP220 (3) (Core) 

CP214 (3:1) (Core) 

 Soft Core/Elective (3) 

Optional 

 

Sem 2 (Jan-Apr) 

CP230 (2:1) (Core) 

Soft Core/Elective (3) 

Soft Core/Elective (3) 

Soft Core/Elective (3)  

CP210 (0:1) Core 

Assignment of Thesis Project Advisor 

Summer (May-July) 

 

 

 

 

 

Internship/Thesis Project 

Sem 3 (Aug-Dec) 

Soft Core/Elective (3) 

Soft Core/Elective (3) 

 

 

Thesis Project (11) 

Placement Interviews 

Sem 4 (Jan-Apr) 

Soft Core/Elective (3) 

 

 

 

Industry/Thesis Project (15) 

 

Notes: 

  1. 17 Credits are from the mandatory (Core) courses  
  1. List of Soft-Core courses is below 
  1. Electives can be any course offered in IISc (with due permission of the instructor)  

Final project CP 299 will focus on research or technology innovations/development for industrial or research problems, and will include a mix of analysis, design and implementation. 

Program Details 

Note: Explanation of the credits 

a:b => ‘a’ hours/week of lectures and  ‘b’x 3 hours/week of laboratory work. 

Core Courses: 

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 

CP280 

Experimental Techniques for Robotics& automation 

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

1:2 

Suresh Sundaram 

Jan-Apr 

CP210 

Seminar 

Exposure to latest topics in research and industry 

0:1 

Pushpak Jagtap 

Jan-Apr 

 

Soft Core courses: 

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 

3:1 

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 

Sensor Front ends, Actuators, Motors and Motor Drives, EMI/EMC, Sensor Noise and data conversion, Imaging/acoustic/infrared/lidar/radar transducers 

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 

Robotic Perception 

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 

 

The same course is being offered with a different course code CP 275 with different credits 2:1 

CP275 

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. 

 

2:1 

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 

 

 

 

 

 

 

CP282 

Field Robotics 

Competition Style, Team Based Robotics Project 

1:2 

Bharadwaj Amrutur/Suresh Sundaram/Pushpak Jagtap 

Changed from Summer to 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 

 

Laboratory Modules (will be embedded in the courses as well as in CP280): 

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 

Relevance and Need of the Program 

Robotics and autonomous systems are an integral part of Industry 4.0 and robotic automation will see an exponential growth in the future. The shortage of skilled labor in transport, agriculture, and supply chain management; operations in hazardous environment like mines and waste processing and recovery; remote monitoring, space explorations and defense will drive the future of robotic automation solutions. Co-design of Cyber and Physical components of such systems and their safe operation along with humans in unstructured and uncertain environments will be key characteristics of such systems. 

Robotics and Autonomous Systems have also changed over the last decade – with the confluence of AI/ML with cheap sensors/Actuators and Battery technologies 

With substantial investments by the Govt of India and Govt. Of Karnataka in this area at IISc through the AI & Robotics Park Initiative (ARTPARK), as well as investments from companies like Cisco, Nokia, Garrett etc. via CSR grants – IISc has started developing state of the art experimental facilities in Connected Robots and Autonomous Systems. These facilities to not only support our research, but also develop rich experiential/laboratory-based training programs for the students. 

Robotics and Autonomous System has always fascinated our UG students as evidenced by their keen participation in many robotic competitions. However, there is no comprehensive course program in this domain in the country that can train then in the foundational aspects as well as the experimental aspects of the subject.  

Key Learning Outcomes of the program 

  • Foundational concepts in Mathematical Foundations like Linear Algebra, Computational Techniques, Probability and Statistics, Control & Optimization, Statistical Signal Processing, Planning & Decisions, Stochastic and Data driven Control, AI for Robotics, Dynamics & Kinematics, Formal Techniques for CPS 
  • Applied concepts in Networking for Robotics & Autonomous Systems, Real-Time Embedded Systems, Sensing & Actuation Systems, Applied Machine Learning for Speech & Vision, Reinforcement Learning for Robot Control, Swarm & Team Robotics, Human-Machine Interactions & social robotics, Security, Safety & Privacy for Autonomous Systems, Autonomous ground/air Robots, Navigation & Guidance, Perception via Signal & Image Processing  
  • Experiential learning via laboratory modules for: Mobile robot programming, Control of Industrial Robot Arms, Programming of Legged Robots, Programming of Drone Systems, Tele-Robotics, Secure Data Pipelines, Robot Simulation Frameworks, VR/AR & Speech Interfaces for Robots, ROS/ROS2 Software stacks, Machine Learning for Robots, Robot hardware for Sensor & Actuator Systems, 3D Design and Prototyping for Robotics, Drone Piloting, Game engine programming, GPU Programming.  

About RBCCPS 

RBCCPS under Div. Of Inter-Disciplinary Sciences, is in a unique intersection of Div. Of EECS and Mechanical Sciences and hence can offer such training spanning both the disciplines – and will be the pillar of this program. ARTPark (AI & Robotics Technologies Park) has been incubated by RBCCPS and will provide laboratory support. 

How will this program benefit Industry? 

Graduates will have a good exposure to foundational and applied topics in Robotics and Autonomous Systems. Hands on exposure to engineering with robots – including mechanical prototyping, ROS/ROS2 programming, AI/ML based programming, VR/AR and other HCI Technologies, 5G and WiFi6 experimentation, indoor and outdoor ground, and aerial robot experiences, will make them well rounded and prepared for many industry problems. They will be able to contribute effectively to create innovative technologies and products in the emerging AI & Robotics applications in industry 4.0, medical, agriculture, mining, defense, smart cities etc.  

How will this program benefit academia? 

Good theoretical and practical grounding will prepare the graduates of this program to participate in innovative experimental research in Robotics and Autonomous Systems. 

Target Audience 

Students with UG/PG background in EE, ECE, CS, Mech, Aero and related fields 

Target Stakeholder Beneficiaries 

Industries in Robotics and Autonomous Systems like: ABB, Bosch, TCS, Wipro, GE, Defense PSUs, Amazon, Flipkart, Target, Nokia, Google, CAIR, ADA, NAL, Intel, Siemens, etc. and many startups 

Research Labs in academia like in IISc and IITs. 

Laboratory Facilities:  

  • Robot Arms,  
  • Indoor Mobile Robots & Drones,  
  • Outdoor Mobile Robots & Drones,  
  • Outdoor autonomous driving testbed  
  • Indoor Connected Robots Lab  
  • Humanoid Robots,  
  • Legged Platforms & Treadmills,  
  • Indoor Mocap system,  
  • Indoor Drone Testbed, Windshaping Facility & Indoor Drones,  
  • Ware-house Robotics Testbed,  
  • Electronics and Mechanical Prototyping Facilities 

Fees:  

As per IISc Norms  

Selection:  

  • Background Degree: BE, BTech, BS (4years)/Equivalent with Gate about cutoff. 
  • For Ministry of Education (MOE) Scholarship: GATE needed in one of (EE, EC, ME, AE, IN, CS) 
  • Sponsored Candidates: Selection as per institute norms 
  • Selection based on : Gate (70%) + Interview (30%) 

Numbers: 

30/year for first two years – increasing to 50/year post that. Allot 10% for sponsored students. 

 

 

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