Job DescriptionTitle: Robotics Engineer, Motion PlanningIntroContoro Robotics is an Austin-based startup revolutionizing warehouse automation with a cutting-edge autonomous truck unloading solution capable of handling payloads over 60 lbs. Our mission is to deploy reliable, high-throughput robotic systems that solve real logistics challenges daily-beyond proof-of-concept demos. We're seeking a Robotics Engineer specializing in motion planning to own both halves of how our robot moves: the geometric path the arm and gripper take to transport boxes from the trailer to the dropoff zone, and the time-optimal, jerk-limited trajectory that makes that motion fast and reliable. You'll work closely with our Autonomy lead to maximize throughput inside tightly constrained container environments.
Job ResponsibilityPath Generation- Design and implement geometric path planning for a high-DOF manipulator transporting single and multiple boxes through cluttered, partially-occluded container spaces.
- Develop and tune sampling-based and optimization-based planners (e.g., OMPL/RRT-family, CHOMP/TrajOpt) within the MoveIt ecosystem for collision-free, kinematically-feasible motion.
Trajectory Optimization- Turn planned paths into time-optimal, dynamically-feasible trajectories that minimize cycle time while respecting velocity, acceleration, jerk, and torque limits of the arm and payload.
- Ensure smooth, jerk-limited motion that protects payload stability (no dropped or shifted boxes) and hardware longevity; handle near-singularity and joint-limit edge cases without stalls or unsafe motion.
Collision & Environment Awareness- Integrate perception outputs (container frame, box poses, occupancy) into the planning scene; reason about collision objects such as container walls, ceiling, and neighboring boxes.
Integration & Validation- Integrate path and trajectory generation with the control stack (MoveIt / ros_control); validate on real hardware and measure cycle-time and throughput impact.
- Collaborate with the Autonomy lead, Orchestration, Perception, and Controls to deliver end-to-end motion that is both fast and reliable across diverse box configurations.
Qualification/RequirementsExperience: 3+ years of professional experience in motion planning, trajectory optimization, or manipulator control, with production or real-hardware deployment.
Education: Minimum B.S. in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field (or equivalent industry experience).
Technical Expertise:- Proficient in C++ (modern standards), Python, and ROS 1/ROS 2.
- Hands-on with MoveIt and motion planning frameworks (OMPL, sampling-based planners such as RRT/RRT-Connect/PRM, and/or optimization-based planners such as CHOMP/TrajOpt).
- Hands-on with time-optimal trajectory generation and time parameterization (e.g., TOTG/TOPP-RA, Ruckig, jerk-limited/S-curve profiles).
- Strong grasp of manipulator kinematics and dynamics-forward/inverse kinematics, collision checking, velocity/acceleration/jerk and torque constraints, singularity and joint-limit handling for 6/7-DOF arms.
- Experience integrating perception inputs (point clouds, object poses, occupancy maps) into collision-aware planning, and validating cycle-time improvements on hardware.
Soft Skills:- Strong problem-solving skills and data-driven decision-making.
- Excellent communication-capable of presenting complex technical concepts clearly to cross-functional teams.
Preferred/Plus- Experience with industrial manipulators (e.g., KUKA) and real-time joint control.
- Background in optimization-based motion (optimal control, QP/NLP-based trajectory optimization).
- Experience planning for multi-object or multi-pick manipulation.
- Experience optimizing for throughput/cycle-time in a production robotics or logistics setting.
- Exposure to physics-based or kinematic simulation for planning validation (Isaac Sim, Gazebo, MuJoCo, Bullet).
