Rakshith Baskar

Robotics Systems Engineer specializing in Autonomous Vehicle Deployment and Real-Time Middleware. Expert in optimizing ROS 2 Humble stacks, tuning DDS Quality of Service (QoS) for low-latency communications, and developing Physical AI interfaces. Proven track record in bridging high-level reasoning with low-level actuator control on heterogeneous ARM/x86 platforms.

Student Research Assistant (Autonomous Systems) at ASU BELIV Lab (2025-05 – Present)

Autonomous Systems Research at Arizona State University under Prof. Junfeng Zhao

• Utilized the Dataspeed Drive-by-Wire (DBW) kit and ROS 2 Python scripts on Linux to bridge a Ford Mach-E with Autoware, performing kinematic mapping that enabled successful autonomous lane-keeping tests on the vehicle
• Performed intrinsic/extrinsic sensor calibration for LiDAR-Camera suites; executed fusion tests to validate spatial synchronization and object detection accuracy within the perception stack
• Optimized ROS 2 middleware on Linux by reconfiguring DDS QoS profiles (Reliability, Durability, History) across the Ethernet backbone between Nuvo and NVIDIA AGX Orin, which improved message reliability and reduced communication delays in the autonomous stack
• Resolved communication overhead for high-bandwidth LiDAR point clouds by tuning transport descriptors, reducing end-to-end latency by 22% during vehicle operation

Graduate Lab Assistant (Systems Engineering) at Arizona State University (2025-01 – 2025-05)

Technical Diagnostic Lead for Master's students in systems engineering

• Served as Technical Diagnostic Lead, troubleshooting software-hardware integration issues for Master's students using CAN Bus and PID/MPC tools, and delivered root-cause analyses that restored robot functionality and kept project timelines on track
• Managed a fleet of 15 Rosmaster X3 robots; performed rapid Hardware-in-the-Loop (HiL) diagnostics to resolve motor de-synchronization, sensor faults, and communication errors
• Developed standardized Python scripts for automated system-health checks, reducing robot maintenance downtime by 30% for classroom laboratories
• Mentored students in configuring Linux Ubuntu 18.04 and setting up multi-robot ROS 2 namespaces, enabling them to launch experiments independently and improve lab productivity

Research Intern (Robotics Manipulation) at MAEDA Lab (Yokohama National University) (2023-12 – 2024-03)

Robotics manipulation research focused on motion planning and Digital Twin synchronization

• Developed motion planning pipelines for Denso and Cobotta manipulators using MoveIt 2, optimizing trajectory generation for high-precision 3D printing tasks in C++
• Built custom RViz 2 visualizations in ROS 2 to monitor real-time state estimation and TF trees during multi-axis operation, reducing debugging time and improving operator awareness
• Engineered structural simulations in MATLAB to analyze robotic end-effector stress, resulting in a 25% reduction in deformation through optimized control gains
• Integrated Force-Torque (F/T) sensors via low-level feedback loops to enable sensitive contact detection during assembly tasks, improving placement repeatability by 15%
• Collaborated with Japanese researchers to document manipulation protocols, resulting in a robust codebase for high-fidelity Digital Twin synchronization

M.S. in Robotics and Autonomous Systems (Systems Engineering) – Arizona State University (2024-08 – 2026-05)

B.Tech in Computer Science Engineering (AI and Robotics) – Vellore Institute of Technology (2020-07 – 2024-07)