Robot Motion Control Engineer

Job Responsibilities

• Responsible for the design, development, debugging, and optimization of robot motion control-related modules, supporting the robot's stable movement, posture adjustment, and contact operations in real scenarios.
• Responsible for the development and integration of control interfaces for robot motion units such as robotic arms, end effectors, waist, lower limbs, or mobile platforms.
• Responsible for building capabilities in trajectory generation, motion execution, posture control, speed control, force control, and compliance control for robot operation tasks.
• Responsible for the kinematic modeling of robotic arms and end tools, coordinate system calibration, trajectory planning, and execution control, improving the stability of operations such as gripping, pushing, pulling, pressing, and handling.
• Responsible for the development of force-position hybrid control, impedance control, admittance control, or related control strategies for robots in contact tasks, to reduce contact impact and operation failure rates.
• Responsible for building the robot's whole-body coordinated movement capabilities, supporting the coordinated control of the upper limbs, torso, waist, lower limbs, or mobile platform in complex operational tasks.
• Responsible for interfacing the motion control module with perception, SLAM, task planning, and systems engineering modules, and for ensuring a closed-loop link from target recognition and motion planning to action execution.
• Responsible for on-robot debugging, fault diagnosis, parameter tuning, and performance optimization, improving system stability and reproducibility in real-world tasks.
• Participate in motion-control validation, trajectory playback, collision detection, and manipulation-strategy testing in simulation, then bring validated control solutions onto physical robots.
• Support the engineering implementation of robots from prototype verification to scenario-based deployment, improving the success rate, safety, and delivery capability of operational tasks.

1. Basic General Ability (Base)

• Proficient in Linux/Ubuntu development environments, with experience in robot system development and on-robot debugging.
• Proficient in C and Python, with good skills in code structure design, debugging, and engineering implementation.
• Familiar with the ROS / ROS2 system, understanding common mechanisms such as Topic, Service, Action, TF, parameter management, and rosbag.
• Master the basics of robot kinematics, including forward and inverse kinematics, Jacobian matrix, coordinate transformation, SE(3), quaternions, and pose calculation.
• Familiar with common motion planning and trajectory generation methods, capable of completing trajectory planning, interpolation, smoothing, and constraint handling for robotic arms or mobile robots.
• Understand the fundamentals of robot dynamics and control, and be familiar with common methods such as PID, feedforward control, state feedback, torque control, and impedance control.
• Possess real robot or robotic arm debugging experience, able to handle engineering issues such as unstable trajectories, vibrations, limit exceedances, collisions, and force control abnormalities.
• Proficient in using Git, with good coding standards, documentation habits, testing awareness, and the ability to collaborate across modules.

2. Specialized Technical Directions (meeting one or more)

Track A: Robotic Arm Manipulation and End-Effector Control

• Familiar with robotic arm kinematics, inverse solution solving, trajectory planning, end-effector pose control, and collision constraint handling.
• Familiar with control methods in robotic arm operations such as grasping, clamping, pushing and pulling, pressing, and handling.
• Capable of completing coordinate system calibration, kinematic modeling, and control adaptation for end tools, fixtures, long-handled tools, and other peripherals.
• Has experience in end-effector alignment, trajectory correction, and closed-loop execution based on visual or point cloud results.
• Experience with tools such as MoveIt, Pinocchio, Drake, KDL, RBDL, MuJoCo, Isaac Sim, etc. is preferred.

Track B: Force and Compliance Control

• Familiar with contact control methods such as hybrid position-force control, impedance control, admittance control, and compliance control.
• It can determine contact states and adjust control based on six-dimensional force sensors, joint torque, current feedback, or tactile information.
• Has experience with contact-type operations such as door pushing and pulling, button pressing, tool grasping, and object handling.
• Able to handle issues such as friction, sticking, rebound, collision, and force control divergence in real-world environments.
• Experience in high-frequency control loops, real-time control, control parameter tuning, and system stability analysis is preferred.

Track C: Whole-Body Motion and Coordinated Control

• Familiar with the full-body motion control problems of mobile robots, humanoid robots, quadruped robots, or mobile robotic arms.
• Understand issues related to robot center of mass control, balance control, support constraints, joint limits, torque constraints, and posture stability.
• Able to coordinate the robotic arm, torso, waist, lower limbs, or mobile platform to complete complex actions.
• Experience in full-body motion planning, Whole-Body Control, MPC, QP control, and trajectory optimization is preferred.
• Experience with on-site debugging of humanoid robots, quadruped robots, and mobile manipulation robots is preferred.

Track D: Motion-Control System Integration and On-Site Debugging

• Possess experience in robot control link integration, capable of completing the full loop of 'planning command—controller—actuator—status feedback'.
• Familiarity with actuator or controller interfaces such as EtherCAT, CAN/CAN-FD, serial port, UDP, and vendor SDK is preferred.
• Able to develop tools for motion status monitoring, trajectory playback, control logging, fault diagnosis, and safety protection.
• Able to complete control parameter tuning, problem reproduction, log analysis, and performance optimization on real robots.
• Experience with on-robot debugging and taking prototype demos through to stable systems is preferred.