Remote job
Kinematics, Planning & Control Engineer
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About this role
Role overview Develop motion and control methods for precise robotic manipulation, from mathematical models and constrained planning to real-time execution. The work includes simulation and hardware validation, with a focus on producing behaviour that is stable, measurable, and safe under relevant constraints.
Responsibilities - Model serial, redundant, cable-driven, and constrained robotic arms. - Implement forward and inverse kinematics, Jacobians, calibration, singularity handling, and redundancy resolution. - Develop solvers that enforce motion constraints such as remote-centre, tool-axis, joint-limit, and workspace requirements. - Generate and optimise smooth, precise trajectories that account for collisions. - Build Cartesian, task-space, visual-servo, impedance, or admittance controllers. - Integrate real-time execution with safety supervision, recovery logic, behaviour trees, and hardware interfaces; compare approaches and analyse failures.
Requirements - Strong C++ and Python programming skills. - Solid understanding of robot kinematics, dynamics, Jacobians, and coordinate transformations. - Experience implementing inverse kinematics, trajectory generation, or robot controllers. - Knowledge of constrained optimisation and real-time numerical methods. - Experience integrating simulators, sensors, actuators, and low-level robot interfaces. - Ability to reproduce research methods and validate them with measurable experiments. ROS 2 experience is useful, alongside knowledge that applies beyond one framework.
Nice to have - Experience with analytical or differential inverse kinematics, hierarchical quadratic programming, nonlinear optimisation, direct collocation, or model-predictive control. - Familiarity with operational-space, impedance, or admittance control. - Work involving remote-centre constraints, redundant manipulators, visual servoing, force control, cable-driven mechanisms, or safety-critical robots.
The engineer will own work across modelling, solver selection, control, testing, and hardware integration, and help establish how to verify precision and stability.