# Perception Algorithms for Autonomous Systems

- Institution: IIT Kanpur
- Department: Multidisciplinary
- Teacher: Prof. Anirban Roy
- Level: Undergraduate
- Language: English
- Subjects: Computer science
- Source: [NPTEL](https://nptel.ac.in/courses/127104001)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/127104001)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

This course will provide detailed introduction of Environment perception algorithm block chain for autonomous platforms such as, Drone/Unmanned aerial vehicles (UAVs), Autonomous driver assistance systems (ADAS), Unmanned ground vehicles (UGVs) etc. Autonomous platforms gather perception information of the environment through multiple sensors measurements such as, Radar (FMCW/Phased array/Pulse Doppler), EO/IRST, Multi-function Camera and Lidar (MFCL), ultrasonics etc. This course will encompass 3 major object/target information processing stages as part of entire perception algorithm modules - Data-association and Multi Object tracking, Multi Sensor data and information fusion and Target classification. The course will focus on fundamentals of various estimation techniques like Maximum likelihood, Maximum-a- posteriori and Kalman filtering and its application to target tracking and sensor fusion.

Prerequisites: Primarily for ME/Ph.D with Control system or Signal Processing related specialization. However, BE (4th year) in EE, ETC or Automobile and Aerospace Engineering can also opt it as open elective.

## Lectures

1. [Lecture 1 - Introduction to Autonomous Systems](https://invisiblenetwork.ai/learn/nptel/127104001/62a6796d0e61) (YouTube)
2. [Lecture 02 : Introduction to Autonomous Systems (Military Use Cases)](https://invisiblenetwork.ai/learn/nptel/127104001/d844a2eaac9f) (YouTube)
3. [Lecture 03: Review of Estimation Paradigms : The Least Square Fit (1st Order , 2nd Order and 3rd Order Fit ))](https://invisiblenetwork.ai/learn/nptel/127104001/6974c23df9b0) (YouTube)
4. [Lecture 04: Prerequisite of Kalman Filter (Repeat) Kalman Filter Fundamentals](https://invisiblenetwork.ai/learn/nptel/127104001/40457f468a59) (YouTube)
5. [Lecture 05: Kalman Filter Properties](https://invisiblenetwork.ai/learn/nptel/127104001/d434317ac00c) (YouTube)
6. [Lecture 06: Target Dynamics Model (Maneuvering & Non-Maneuvering)](https://invisiblenetwork.ai/learn/nptel/127104001/6c60f29a1f65) (YouTube)
7. [Lecture 07: Sensor Measurement Model and False Alarm Simulation](https://invisiblenetwork.ai/learn/nptel/127104001/a1b3919cd68e) (YouTube)
8. [Lecture 08: Non linear Kalman Filter Family --- The Extended Kalman Filter](https://invisiblenetwork.ai/learn/nptel/127104001/82470ee081f9) (YouTube)
9. [Lecture 09: Non linear Kalman Filter Family --- The Pseudo-measurement Kalman Filter](https://invisiblenetwork.ai/learn/nptel/127104001/222aea0047fa) (YouTube)
10. [Lecture 10: Pseudo-linear Kalman Filter and Extended Kalman Filter Application In Bearing Angle Only Tracking Problem](https://invisiblenetwork.ai/learn/nptel/127104001/8311ab1ff25f) (YouTube)
11. [Lecture 11: Bearing Angle Only Tracking Problem (contd.) Comparison – PMF vs EKF](https://invisiblenetwork.ai/learn/nptel/127104001/5a1f5d443a5a) (YouTube)
12. [Lecture 12: Statistical linearization and The Unscented Kalman Filter](https://invisiblenetwork.ai/learn/nptel/127104001/25eddbcea7a7) (YouTube)
13. [Lecture 13: Summary – Explained in Board](https://invisiblenetwork.ai/learn/nptel/127104001/e048935f7c78) (YouTube)
14. [Lecture 14: Introduction to Tracking & Challenges to Multi-Target tracking](https://invisiblenetwork.ai/learn/nptel/127104001/4e2a9b71b6ac) (YouTube)
15. [Lecture 15 (Part A): Multi-Target Tracking stages](https://invisiblenetwork.ai/learn/nptel/127104001/b9aa1bf9c74a) (YouTube)
16. [Lecture 15 (Part B): Multi-Target Tracking stages (Contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/47ed0675e23f) (YouTube)
17. [Lecture 16: Nearest Neighbour hood association and Example](https://invisiblenetwork.ai/learn/nptel/127104001/9b5d878fb8d5) (YouTube)
18. [Lecture 17 (Part A): Theory of Probabilistic Data Association](https://invisiblenetwork.ai/learn/nptel/127104001/c5226f165ac8) (YouTube)
19. [Lecture 17 (Part B): Theory of Probabilistic Data Association (Contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/e1a658cad9b8) (YouTube)
20. [Lecture 18: PDAF Implementation including Track Coalescence Problem & Solution](https://invisiblenetwork.ai/learn/nptel/127104001/4bc45e4d2297) (YouTube)
21. [Lecture 19: Multi Hypothesis Tracking](https://invisiblenetwork.ai/learn/nptel/127104001/75811f303b74) (YouTube)
22. [Lecture 19 (Part B): Multi Hypothesis Tracking](https://invisiblenetwork.ai/learn/nptel/127104001/98953ff65096) (YouTube)
23. [Lecture 20: Hypothesis Oriented MHT implementation](https://invisiblenetwork.ai/learn/nptel/127104001/d70f90d62035) (YouTube)
24. [Lecture 21: Track-Oriented MHT Concept](https://invisiblenetwork.ai/learn/nptel/127104001/5d743ebce3a2) (YouTube)
25. [Lecture 22 - Part A: Implementation of Track Oriented MHT](https://invisiblenetwork.ai/learn/nptel/127104001/0c5d4c6f2d1d) (YouTube)
26. [Lecture 22 - Part B: Implementation of Track Oriented MHT (Contd)](https://invisiblenetwork.ai/learn/nptel/127104001/3269a407515d) (YouTube)
27. [Lecture 23: Multi-target tracking Algorithm Performance Comparisons](https://invisiblenetwork.ai/learn/nptel/127104001/df96880a2db0) (YouTube)
28. [Lecture 24: MHT Performance Indices](https://invisiblenetwork.ai/learn/nptel/127104001/29b9d94d01ca) (YouTube)
29. [Lecture 25: Optimal Sub-Pattern Assignment Metric](https://invisiblenetwork.ai/learn/nptel/127104001/51856012ba32) (YouTube)
30. [Lecture 26 - Part A: Concept of Maneuvering Target Tracking and stochastic Hybrid System](https://invisiblenetwork.ai/learn/nptel/127104001/1cd31900fe4d) (YouTube)
31. [Lecture 26 - Part B: Concept of Maneuvering Target Tracking and stochastic Hybrid System (Contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/c2413a63e3d3) (YouTube)
32. [Lecture 27: Interacting Multiple Model Algorithm for Maneuvering Target Tracking Stages](https://invisiblenetwork.ai/learn/nptel/127104001/1d163fd32520) (YouTube)
33. [Lecture 28: Problems and Solution for IMM Algorithms](https://invisiblenetwork.ai/learn/nptel/127104001/c774264c57f1) (YouTube)
34. [Lecture 29: Example of IMM tracking](https://invisiblenetwork.ai/learn/nptel/127104001/20a725c4c69a) (YouTube)
35. [Lecture 30 - Part A: Application of IMM algorithm for GPS Navigation Problem](https://invisiblenetwork.ai/learn/nptel/127104001/2be5c22a026d) (YouTube)
36. [Lecture 30 - Part B: Application of IMM algorithm for GPS Navigation Problem (Contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/920a4f3cd0e5) (YouTube)
37. [Lecture 31 - Part A: GPS Navigation Problem (contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/d8ae70d5424c) (YouTube)
38. [Lecture 31 - Part B: GPS Navigation Problem (contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/01bbed47815c) (YouTube)
39. [Lecture 32: ((GPS Navigation Problem (contd.))](https://invisiblenetwork.ai/learn/nptel/127104001/90771ebd43e3) (YouTube)
40. [Lecture 33: Problems related to target tracking](https://invisiblenetwork.ai/learn/nptel/127104001/79de18c5843e) (YouTube)
41. [Lecture 34: Continuous Kalman Filter Problems](https://invisiblenetwork.ai/learn/nptel/127104001/a230bd04583b) (YouTube)
42. [Lecture 35: Information Filter Problem](https://invisiblenetwork.ai/learn/nptel/127104001/3eda2b939fbe) (YouTube)
43. [Lecture 36: Implementation of Cramer Rao Lower Bound in target tracking Problems](https://invisiblenetwork.ai/learn/nptel/127104001/53558548eedb) (YouTube)
44. [Lecture 37: Problems on Bearing Angle only Target Tracking](https://invisiblenetwork.ai/learn/nptel/127104001/a8eec1cf23dd) (YouTube)
45. [Lecture 38: Bearing Angle Only Target Tracking Problem (contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/df2dec29e52e) (YouTube)
46. [Lecture 39: Part 1 - Introduction to Sensor Fusion](https://invisiblenetwork.ai/learn/nptel/127104001/66e8c1ec189e) (YouTube)
47. [Lecture 39: Part 2 - Introduction to Sensor Fusion (Contd)](https://invisiblenetwork.ai/learn/nptel/127104001/6ae9bbc9c377) (YouTube)
48. [Lecture 40: Problems Of Measurement Fusion](https://invisiblenetwork.ai/learn/nptel/127104001/23fae47d7210) (YouTube)
49. [Lecture 41: Recursive Estimation using Bayes principle](https://invisiblenetwork.ai/learn/nptel/127104001/28348647938a) (YouTube)
50. [Lecture 42: Kalman Filter Based Measurement Augmentation](https://invisiblenetwork.ai/learn/nptel/127104001/b55864646641) (YouTube)
51. [Lecture 43: Controller based Measurement Augmentation- Spacecraft Attitude Estimation & Control](https://invisiblenetwork.ai/learn/nptel/127104001/24a915c209db) (YouTube)
52. [Lecture 44: Part 1 - Controller based Measurement Augmentation - Baro Altimeter Fusion](https://invisiblenetwork.ai/learn/nptel/127104001/abc0aac3d2a3) (YouTube)
53. [Lecture 44: Part 2 - Controller based Measurement Augmentation - Baro Altimeter Fusion (Contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/9f130512aa62) (YouTube)
54. [Lecture 45: Complementary Filter & CBR](https://invisiblenetwork.ai/learn/nptel/127104001/58dd25602ee2) (YouTube)
55. [Lecture 46: State Vector Fusion](https://invisiblenetwork.ai/learn/nptel/127104001/9262c4457ed2) (YouTube)
56. [Lecture 47: Decentralized State Vector Fusion](https://invisiblenetwork.ai/learn/nptel/127104001/04825a341721) (YouTube)
57. [Lecture 48: Error Ellipse using Covariance matrix](https://invisiblenetwork.ai/learn/nptel/127104001/7bbc5edf657a) (YouTube)
58. [Lecture 49 Part A: Introduction to Classification and Machine learning techniques](https://invisiblenetwork.ai/learn/nptel/127104001/634704bbc191) (YouTube)
59. [Lecture 49 Part B: Introduction to Classification and Machine learning techniques (Contd.)](https://invisiblenetwork.ai/learn/nptel/127104001/7e47bf90d4b1) (YouTube)
60. [Lecture 50: Supervisory learning process flow & Methodologies](https://invisiblenetwork.ai/learn/nptel/127104001/7566ee5f597a) (YouTube)
61. [Lecture 51: Supervisory learning Methodologies (Naïve Bayes Classifier Example)](https://invisiblenetwork.ai/learn/nptel/127104001/e2cb380328ab) (YouTube)
62. [Lecture 52: Supervisory learning Methodologies (Linear Regression)](https://invisiblenetwork.ai/learn/nptel/127104001/7f29d94abc64) (YouTube)
63. [Lecture 53: Part A - Supervisory learning Methodologies (Linear Regression Tree)](https://invisiblenetwork.ai/learn/nptel/127104001/2c81cfd13878) (YouTube)
64. [Lecture 53: Part B - Supervisory learning Methodologies (Linear Regression Tree) Contd.](https://invisiblenetwork.ai/learn/nptel/127104001/3462f30adc69) (YouTube)
65. [Lecture 54: Supervisory learning Methodologies (Logistic Regression)](https://invisiblenetwork.ai/learn/nptel/127104001/5a982eb9a2a4) (YouTube)
66. [Lecture 55: Logistic Regression Solution Mechanism](https://invisiblenetwork.ai/learn/nptel/127104001/579c519b5dda) (YouTube)
67. [Lecture 56: Support Vector machine](https://invisiblenetwork.ai/learn/nptel/127104001/5da24b7d28be) (YouTube)
68. [Lecture 57: Support Vector Classifier and Support Vector Machine](https://invisiblenetwork.ai/learn/nptel/127104001/a85f517211c3) (YouTube)
69. [Lecture 58: SVM Optimization solution](https://invisiblenetwork.ai/learn/nptel/127104001/659f36da13c3) (YouTube)
70. [Lecture 59: Fundamentals of Neural Network based classifiers](https://invisiblenetwork.ai/learn/nptel/127104001/545841b5f4a6) (YouTube)
71. [Lecture 60: Convolutional Neural Network](https://invisiblenetwork.ai/learn/nptel/127104001/cdf310369450) (YouTube)
72. [Lecture 61: Bias-Variance trade-off in Machine learning](https://invisiblenetwork.ai/learn/nptel/127104001/c2e53418b949) (YouTube)
73. [Lecture 62: Miscellaneous (Problems)](https://invisiblenetwork.ai/learn/nptel/127104001/dbcae360aeab) (YouTube)
74. [Lecture 63: Part 1 - Miscellaneous (Problems)](https://invisiblenetwork.ai/learn/nptel/127104001/7efebbfb26b7) (YouTube)
75. [Lecture 63: Part 2 - Miscellaneous (Problems) Contd.](https://invisiblenetwork.ai/learn/nptel/127104001/327fc572e4dc) (YouTube)
76. [Lecture 64 - Conclusion (few practical DTC Systems)](https://invisiblenetwork.ai/learn/nptel/127104001/2a7c33ab36d9) (YouTube)