12/01/2021
By Sokny Long

The Francis College of Engineering, Department of Electrical and Computer Engineering, invites you to attend a doctoral dissertation proposal defense by Sharath Patil on “Differentiation Based Peak Detection for Fast and Compact LiDar Systems.”

Ph.D. Candidate: Sharath Patil
Defense Date: Wednesday, Dec. 15, 2021
Time: 11:30 a.m. to 1 p.m.
Location: Ball Hall 301 Conference Room. This will be a hybrid (in-person with virtual component). Those interested in attending should contact, sharath_patil@student.uml.edu, and committee advisor, martin_margala@uml.edu, at least 24 hours prior to the defense to request access to the meeting.

Committee Chair (Advisor): Martin Margala, Professor, Department of Electrical & Computer Engineering, UMass Lowell

Committee Members:

  • Joyita Dutta, Associate Professor, Department of Electrical & Computer Engineering, UMass Lowell
  • Thanuka Vickramarathne, Assistant Professor, Department of Electrical & Computer Engineering, UMass Lowell
  • Corey Shemelya, Assistant Professor, Department of Electrical & Computer Engineering, UMass Lowell
  • Paul Robinette, Assistant Professor, Department of Electrical & Computer Engineering, UMass Lowell

Brief Abstract:
Autonomous vehicles are ubiquitous in several applications like warehousing, automotive, etc., the latter gaining popularity and acceptance in recent years. Autonomous vehicles rely on several sensors to help their navigation to a certain destination. This might include avoiding collisions with obstacles in air or on the road or even on water depending on where they are deployed. One of the main challenges for an autonomous vehicle is to detect if there is an obstacle in its path and automatically maneuver to avoid hitting an object. Several sensors are used for collision avoidance depending on the requirements- speed, resolution, cost, power, etc. The sensor solution that provides the best compromise for the above requirements is usually chosen. Several autonomous vehicles utilize Sensor Fusion to utilize data from complimentary sensors with sophisticated algorithms to process the data and _nd the ground truth. An example of a sensor fusion system might involve Radar, LiDar and Sonar sensor systems.

This work describes a novel approach of using differentiation to detect the peak location in the received LiDAR signal and demonstrates the effectiveness of the method on a single chip solution. The proposed method can improve the footprint of the analog signal chain by 30% thereby saving the overall chip area, but with a performance trade-off for signals with low SNR. The distance measurement accuracy of this method is being compared to the standard methods which use high-resolution, high-speed ADCs. The designed system doesn't have an ADC, but pulse detection mechanism has been implemented using an array of sample and hold capacitors followed by a comparator, on a PCB. The performance of a comparator-based pulse detection has been compared to an ADC-based pulse detection. The control circuitry and data processing are implemented using Xilinx ZYNQ-based FPGA.

All interested are welcome to attend.