The paper presents a multiple task-priority inverse kinematics algorithm for a dual-arm aerial manipulator. Both tasks defined as equality constraints and inequality constraints are handled by means of a singularity robust method based on the Null-Space based Behavioral control. The proposed schema is constituted by the inverse kinematics control, that receives the desired behavior of the system and outputs the reference values for the motion variables, i.e. the UAV pose and the arm joints position, and a motion control, that computes the vehicle thrusts and the joint torques. The method has been experimentally validated on a system composed by an underactuated aerial hexarotor vehicle equipped with two lightweight 4-DOF manipulators, involved in operations requiring the coordination of the two arms and the vehicle.

This paper presents the motion planning of a novel aerial robotic system with a long-bar extension and two arms for long-reach manipulation in cluttered environments. The novel aerial long-reach manipulator includes a passive revolute joint between the aerial platform and the dual arm. This feature minimises the torque induced to the aerial system in case of unexpected collisions of the manipulator. The motion planning problem is addressed considering jointly the complete set of configuration variables for the aerial platform and the dual arm. Furthermore, the planner has been built over the fundamentals of RRT* algorithms in order to optimise the performance of the trajectories in terms of energy and time. The proposed planning method has been experimentally validated in a realistic industrial scenario, the transportation of a long bar through a cluttered environment consisting of several pipe structures.