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Shashank Walke
Mid-level Software Engineer specializing in systems, cloud, and applied machine learning
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Robotics software engineer focused on ROS 2 localization/SLAM: built a particle-filter (Monte Carlo) localization system in Python with likelihood-field modeling to handle noisy LiDAR and dynamic environments. Strong in debugging ROS 2 integration issues (tf2 frame sync, DDS/QoS message reliability) and in profiling/optimizing pipelines to reach real-time performance (~10 Hz) using precomputation and KD-trees.
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Key Strengths
- Implemented Monte Carlo Localization in ROS/Python with robust likelihood-field sensor model for noisy LiDAR
- Optimization for fast convergence: adaptive particle counts, low-variance resampling, random particle injection
- Debugged TF map/odom synchronization issues using tf2 buffering/extrapolation and correct timestamp handling
- ROS 2 QoS tuning to prevent message drops (RELIABLE for pose, BEST_EFFORT for high-rate scans)
- Performance profiling-driven SLAM optimization (sensor model was 85% of cycle time)
- Achieved real-time ~10 Hz operation via precomputed likelihood fields and KD-tree nearest-neighbor lookups
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