Robotics Engineer - I

robotic control systems

Core Technical Responsibilities-

Robotics Kinematics & Dynamics

• Forward and inverse kinematics (serial/parallel manipulators, mobile platforms)
• DenavitHartenberg (D-H) parameterization, transformation matrices, SE(3) frames
• Inverse dynamics using Newton-Euler and Lagrangian methods
• Multi-body dynamics modeling, Jacobian computation, singularity handling
• Constraint resolution for underactuated or redundant robotic systems
• Dynamics compensation for payload variation and external disturbances
  

Control Systems Design

• PID, cascaded PID, feedforward + feedback hybrid control
• Linear state-space modeling, controllability and observability analysis
• LQR, pole placement, and optimal trajectory stabilization
• Model Predictive Control (MPC) basics for path tracking
• Sensor feedback loop integration (encoder, IMU, force-torque sensors)
• Saturation, anti-windup, slew rate limiting, and safety interlocks
  

Estimation & Sensor Fusion

• IMU + magnetometer + GPS fusion using complementary filters or Kalman filters (EKF/UKF)
• Dead-reckoning, drift compensation, and heading estimation
• Odometry tracking for differential drive, Ackermann steering, and holonomic bases
• Sensor latency calibration and outlier rejection filters
• Covariance propagation and uncertainty bounding
• SLAM or VIO pipeline understanding (bonus)
  

Math Tools & Simulation

• Proficient in

  Eigen

  for linear algebra (matrices, quaternions, decompositions)
• Use of MATLAB/Simulink, Python (NumPy/SciPy), or C++ math libraries
• Simulation using Gazebo, Isaac Sim, Webots, or custom physics engines
• Motion planning algorithms: A*, RRT, potential fields, trajectory smoothing
• Testing with synthetic sensor injection and disturbance modeling
  

System Integration

• Interface with embedded firmware teams for control loop integration
• Tuning control loops for real-world timing, actuator limits, and environmental response
• Coordinate frame management (NED, ENU, body-fixed, camera frames)
• Deployment onto real-time OS or Linux-based compute nodes (ROS 1/2 stack)
• Real-world calibration procedures: encoder zeroing, IMU alignment, gain tuning
  

Tools & Frameworks

• ROS 1/2 (navigation, tf, control, message transport)
• RViz or 3D visualization tools for debugging
• Git, CMake, and CI pipelines for code validation
• Logging, playback, and telemetry analysis (e.g., rosbag, custom log viewers)
  

Preferred Qualifications

• B.Tech / M.Tech / Ph.D. in Robotics, Control Systems, Mechatronics, or Applied Mechanics
• 3–7+ years of robotics control and estimation experience
• Strong background in applied mathematics and physical modeling
• Experience with robotic arms, mobile robots, UAVs, or hybrid autonomous platforms
• Publications or project contributions in control, planning, or estimation domains