The document discusses the development of a lidar-based obstacle detection system integrated with emergency brake assistance, aimed at enhancing autonomous RC vehicles to prevent accidents. It outlines the design process, hardware components, software analysis using ROS and Python, and provides simulations and results for different scenarios. Future enhancements include integration with advanced driver assistance systems (ADAS) and weight reduction for the RC model car.

1. LIDAR BASED OBSTACLE
DETECTION WITH
DYNAMIC THRESHOLDING
Master’s EMM/Mechatronics – Embedded Project
Presented By:
• Tejashree Bhosale (31637)
• Akash Satamkar (31672)
• Krupali Rana (31668)

2. Outline
 Introduction
 Problem Definition
 Goals
 Block Diagram
 Hardware Analysis
 Design Ergonomics
 Actual Design Model
 Software Analysis
 Flowchart
 Simulations and Results
 Conclusion
 Enhancements and Future scope
 Reference

3. Introduction
 If the obstacle is detected in field of view of Lidar Sensor, then depending on the
steering angle and speed of the vehicle, emergency break assistance or
deceleration of vehicle is performed.
 Emergency and warning distance thresholds vary with speed and steering angle of
the vehicle.
 This prototype can further be integrated to Autonomous RC Model Car to
implement obstacle detection and emergency break assistance system.

4. Problem Definition
 Main purpose - To implement obstacle detection mechanism with emergency
break assistance system in order to avoid accidents due to human errors.
 The implementation should be easily integrable for high scale projects like
Autonomous RC Model Car.

5. Goals
 To detect obstacles in field of view.
 Field of view should change based on direction and steering angle.
 To the process of determining emergency and warning distance threshold based
on speed of the vehicle.
 Speed should decrease as vehicle moves towards the obstacle.
 emergency break should be applied.

6. Block Diagram

7. Hardware Analysis
 Neato LIDAR xv_11
 Raspberry Pi 3 Model B+
 Arduino NANO
 LN293D H-Bridge Motor driver IC
 DC motor
 Batteries and Power Bank
 RC model car chassis
Components

8. Design Ergonomics
 LIDAR mounting position
 Weight balancing on RC model car chassis
 Portable batteries for independent system
Challenges :

9. Actual Design Model
Fig 1. - Side view of actual implemented model
Fig 2. - Top view of actual implemented model

10. Software Analysis
 Why ROS … ?
ROS is light and takes less space on system
ROS packages can be managed by different authors on GIT repositories
Easy to integrate
 Why Python?
Interpreted Language
ROS Python API available
Compact code and user friendly

11. Flowchart

13. Threshold determination
 Emegency Threshold = (speed * speed)/(850 * friction_factor)
 Warning Threshold = Emegency Threshold + 1.2
 Reference:
https://korkortonline.se/en/theory/reaction-braking-stopping/

14. Case 1: Vehicle does not detect obstacle or vehicle is far
beyond warning threshold
Simulations and Results

15. Case 2: Vehicle detects obstacle and crosses warning
distance

16. Case 3: Vehicle detects obstacle and moves towards obstacle
nearer than emergency breaking distance

17. Enhancements and Future scope
 Integration with ADAS model
 Weight Reduction on RC car

18. References
 http://www.tobias-weis.de/neato-xv-laser-scanner-lidar/
 http://wiki.ros.org/xv_11_laser_driver/Tutorials/Running%20the%20XV-11%20Node
 https://scratchrobotics.com/2018/04/25/hacking-xv-11-lidar/
 https://www.youtube.com/watch?time_continue=34&v=6R3rVeY3Sgc
 https://www.engineersgarage.com/electronic-components/l293d-motor-driver-ic

19. Thank you for listening……
Any Questions ?