Sequential motion planning for dual-arm robots

Abstract

This thesis examines sequential motion planning for a dual-arm robotic system in a simulation environment. Dual-arm manipulators are increasingly used in manufacturing and collaborative robotics due to their ability to perform coordinated, human-like manipulation tasks. However, planning motion for two manipulators in a shared workspace increases complexity and introduces a higher risk of collisions.

To address these challenges, a fully sequential motion planning strategy is implemented, where one manipulator is planned and executed at a time while the other remains stationary. The system is developed using ROS 2 for integration, MoveIt for motion planning and collision checking, and Gazebo for simulation. Two Franka FR3 manipulators are configured as separate planning groups, enabling independent control. A handover-style demonstration scenario is used to evaluate the approach, including pickup, transfer, and placement phases.

The results show that the sequential planning strategy provides stable and reliable task execution, achieving consistent performance across repeated runs. However, the approach introduces significant idle time, as only one manipulator is active at a time. This limits overall efficiency and prevents the system from leveraging parallel motion, which is a key advantage of dual-arm robotics.

The study demonstrates that sequential motion planning is a practical and predictable baseline approach for dual-arm coordination, particularly in development and testing environments. At the same time, it highlights the need for more advanced or hybrid strategies to improve efficiency and better utilise both manipulators in shared workspaces.