The complexity and dexterity of the platform requires to investigate planning methods to exploit the capabilities of the robot.
Geometry path planning of rigid robot arms is a well covered today in the literature, however more energy efficient paths or time optimal paths can be planned by exploiting the natural dynamics of the robot.
The dexterity of the hand provides a lot of freedom in the grasp planning process but also creates new computation challenges. Methods such as primitive based planning and reinforcement learning are currently investigated.
Programming a complex robotic system still requires highly skilled and experienced operators. Research in the fields of Dynamic Robot Programming persues the goal of simplifying the programming process by taking advantage of interactive programming, structural patterns and graphical program representation.
 Reinecke, Jens and Dietrich, Alexander and Schmidt, Florian and Chalon, Maxime (2014) Experimental Comparison of Slip Detection Strategies by Tactile Sensing with the BioTac on the DLR Hand Arm System. In: IEEE International Conference on Robotics and Automation (ICRA). ICRA 2014, 31 Mai bis 5.Juni, Hong Kong.
 Chalon, Maxime and Reinecke, Jens and Pfanne, Martin (2013) Online in-hand object localization. In: IEEE RSJ International Conference on Intelligent Robots and Systems. International Conference on Intelligent Robots and Systems, 3-7 November 2013, Tokyo, Japan.