Telenav Autonomous Car Developer - Intern Coding Challenge
Problem Statement
Sensor Fusion Project:
- This project consists of implementation of Sensor Fusion Algorithm using filter with C++.
- You can use any of EKF, UKF, Kalman Filter, Particle Filter for your implementation.
- You have been provided with an input file(SensorFusion-data-1.txt) which contains measurements from real sensors like Radar and Lidar and your task is to output fusion of those input measurements.
Project Description:
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Input file contains iterations. At each iteration, multiple sensor measurments have been taken.
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You have to fuse only measurements from different sensors. Sensor Id : 2 = Radar, Sensor Id : 4 = Lidar
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You can fuse measurements based upon Euclidean Distance between measurements. (Criteria: Euclidean Distance <= 10.0 & absolute delta y = 1.0)
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From each iteration you should only pick up two different sensor measurements for fusion. If there are no measurements available to fuse, you ca- n skip the iteration.
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You need to implement filter in C++, so that you can apply these measurements to produce fused measurements.
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Lidar Measurement Covariance is 0.02 meter.
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Radar Measurement Covariance is 0.1 meter.
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You can assume linearity between measurements during individual iteration.