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Sourabh Tiwari
Mid-level Robotics Software Engineer specializing in ROS2 autonomy and computer vision
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Robotics software engineer from Bigbot who led localization and perception for an outdoor autonomous delivery robot, building ROS2/Nav2-based autonomy with EKF sensor fusion (IMU/odometry/GPS) and perception-driven dynamic costmaps. Experienced taking systems from Gazebo simulation to real-robot deployment, optimizing real-time behavior via logging-driven debugging and latency reduction, and integrating heterogeneous comms (MAVROS/MAVLink, UART/CAN, MQTT) for distributed and multi-robot setups.
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Key Strengths
- Built and integrated core autonomy stack components (localization, navigation, perception) for outdoor delivery robot
- Deep ROS2/Nav2 implementation experience (custom nodes, messages, costmap layers)
- Robust outdoor localization via EKF fusion of IMU, wheel odometry, and GPS
- Improved obstacle avoidance using continuously-updated dynamic costmaps driven by perception
- Real-world debugging approach: log/inspect sensor + costmap data, identify false obstacles/localization drift, tune filters
- Reduced perception latency to maintain consistent real-time updates
- Led localization and perception team and drove integration with broader software stack
- Designed reliable heterogeneous robot communications across edge computers/microcontrollers using ROS2 + MAVLink/UART/CAN/MQTT
- Strong sim-to-real workflow using Gazebo plus Dockerized deployments and automated build/test validation
- Built a custom ROS2 perception stack for autonomous sidewalk delivery robot using depth camera + 2D LiDAR (no 3D LiDAR)
- Designed modular ROS2 architecture with clean node interfaces and performance-optimized custom message types
- Reduced perception latency from ~90ms to ~30ms via vision/depth fusion into a single occupancy grid
- Integrated YOLO segmentation into a real-time ROS2 pipeline on NVIDIA Jetson using TensorRT and shared-memory transport (25–30 FPS)
- Improved navigation reliability: reduced navigation failures by 70%+; system adopted into next prototype
- Robust localization via EKF tuning to handle inconsistent sensor rates and noise (GPS drift, IMU bias) with ICP+GPS+IMU fusion
- Production-minded reliability practices: profiling early, time-bounded modular nodes, watchdog/heartbeat monitoring, real-world stress testing
Reference Highlights
- Strong technical skills
- Strong programming skills
- Strong ROS/ROS2 experience
- Able to build robotics software from scratch
- Good debugging skills
- Works collaboratively with the team
- Effective cross-functional collaborator (hardware/firmware)
- Interpersonal skills
- Leadership quality
- Hardworking
- Best fit for robotics software engineer role
- Expert in robotics (especially AI)
- Designed the full ROS framework for the robots
- Solved AI challenges easily
- Strong debugging ability
- Hands-on testing mindset (tested robots many times)
- Effective at real-time navigation and obstacle avoidance problems
- Able to coordinate/manage a multi-robot platform (around 10 robots)
- Strong teamwork and cross-disciplinary collaboration
- Values accuracy/precision when working with hardware
- Creative thinker (thinks differently)
- Cost-effective/efficient solutions (good results with cheaper sensors)
- Highly talented
- Would be rehired
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