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Thirumalaesh Ashokkumar
Mid-level Robotics Engineer specializing in SLAM, perception, and state estimation
General MotorsUniversity of Michigan4 Years ExperienceMid LevelWorks On-Site
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About
Robotics software lead with 4+ years of ROS/ROS2 experience spanning a startup (Inductive Robotics) and General Motors, building autonomous mobile manipulation and AMR material-handling stacks. Has hands-on depth in SLAM/navigation (Cartographer/Nav2), perception, and simulation, and has directly modified Cartographer to handle real-world sensor dropouts. Currently working on fleet-scale mapping capabilities (map merging/editing, trajectory pruning) for multi-robot deployments.
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Led end-to-end software stack development for an autonomous mobile manipulator (ROS-based SLAM, navigation, manipulation, perception)
Creative software workarounds for hardware/environment constraints (vision-based heading feedback loop in high-friction uneven parking lot)
Deep ROS/ROS2 integration across navigation, SLAM, manipulation, and tooling (Nav2, Cartographer, MoveIt, robot_localization, Gazebo/RViz/rqt)
Strong real-time debugging and root-cause analysis using topic monitoring and sensor/timestamp validation (identified IMU dropouts via rqt gaps)
Ability to modify and extend core open-source robotics packages for robustness (patched Cartographer to fall back to wheel-odom orientation during IMU loss)
Systems-level troubleshooting of estimation behavior and parameterization (identified landmark weight rebasing causing pose jumps; corrected weighting)
Simulation-driven development and demos (custom Gazebo worlds, modified Husky sim, added sensors/plugins)
Improved engineering workflow quality via CI/CD enhancements (added unit tests and baseline performance metrics) and containerized development (Docker)
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Experience
Robotics EngineerGeneral Motors · Jan 2025 – Present
Robotics EngineerInductive Robotics · May 2024 – Oct 2025
Robotics and Software Engineering InternTrossen Robotics · Jul 2024 – Dec 2024internship
Mid-level Robotics Researcher specializing in motion planning and vehicle routing
13y exp
Carnegie Mellon UniversityCarnegie Mellon University
“CMU robotics PhD/PhD researcher and former CMU Robotics Club project lead who built a novel Bayes-filter-based system to localize within music so robotic instruments can follow a human’s tempo in real time. Also works on simulation-heavy multi-agent vehicle routing with traffic-signal scheduling, optimizing for real-time performance via profiling, multithreading, and neural-network surrogates for signal control.”