A variable-fractional order admittance controller for pHRI

In today’s automation driven manufacturing environments, emerging technologies like cobots (collaborative robots) and augmented reality interfaces can help integrating humans into the production workflow to benefit from their adaptability and cognitive skills. In such settings, humans are expected to work with robots side by side and physically interact with them. However, the trade-off between stability and transparency is a core challenge in the presence of physical human robot interaction (pHRI). While stability is of utmost importance for safety, transparency is required for fully exploiting the precision and ability of robots in handling labor intensive tasks. In this work, we propose a new variable admittance controller based on fractional order control to handle this trade-off more effectively. We compared the performance of fractional order variable admittance controller with a classical admittance controller with fixed parameters as a baseline and an integer order variable admittance controller during a realistic drilling task. Our comparisons indicate that the proposed controller led to a more transparent interaction compared to the other controllers without sacrificing the stability. We also demonstrate a use case for an augmented reality (AR) headset which can augment human sensory capabilities for reaching a certain drilling depth otherwise not possible without changing the role of the robot as the decision maker

An ontology for failure interpretation in automated planning and execution

This is a post-peer-review, pre-copyedit version of an article published in ROBOT - Iberian Robotics Conference. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-35990-4_31”.Autonomous indoor robots are supposed to accomplish tasks, like serve a cup, which involve manipulation actions, where task and motion planning levels are coupled. In both planning levels and execution phase, several source of failures can occur. In this paper, an interpretation ontology covering several sources of failures in automated planning and also during the execution phases is introduced with the purpose of working the planning more informed and the execution prepared for recovery. The proposed failure interpretation ontological module covers: (1) geometric failures, that may appear when e.g. the robot can not reach to grasp/place an object, there is no free-collision path or there is no feasible Inverse Kinematic (IK) solution. (2) hardware related failures that may appear when e.g. the robot in a real environment requires to be re-calibrated (gripper or arm), or it is sent to a non-reachable configuration. (3) software agent related failures, that may appear when e.g. the robot has software components that fail like when an algorithm is not able to extract the proper features. The paper describes the concepts and the implementation of failure interpretation ontology in several foundations like DUL and SUMO, and presents an example showing different situations in planning demonstrating the range of information the framework can provide for autonomous robotsPeer ReviewedPostprint (author's final draft

Development of a Calibration Routine for Remotely Controlling a Robotic Hand

Maintenance and de-orbiting of satellites are tasks that are yet to be solved. One of DLR’s approach to this task is to on-orbit servicing is using a telepresence system. High performance telepresence systems enable intuitive interaction with the remote environment. There are several factors influencing the overall performance like the level of immersion of the video display. This work focuses on improving the coupling between the hands, DLR/HIT Hand II, of the remotely located humanoid robot Justin and the hands of the human operator. In order to ensure improved coupling of the two, both the ability of the DLR/HIT Hand II to track given references, and the calibration and mapping of a dataglove, which measures the human hand joint angles, are improved. This is achieved by three main tasks: implementing a friction compensation module with a friction parameter identification routine, designing a controller based on the functionally related systems framework, and developing a calibration routine that handles the calibration and mapping of a dataglove simultaneously. Experiments proved the improvement of the reference tracking ability of the DLR/HIT Hand II and the performance of the calibration and mapping of Cyberglove is verified by subjective opinions of people who have previously operated the telepresence system at DLR without the new calibration

From discrete task plans to continuous trajectories

We present a logic-based framework to provide robots with high-level reasoning, such as planning. This framework uses the action description language C+ to represent actions and changes, and the system CCALC to reason about them. In particular, we can represent action domains that involve concurrent actions and additive fluents; based on this description, we can compute shortest plans to a planning problem that involves cost constraints. We show the applicability of this framework on two LEGO MINDSTORMS NXT robots: we compute a discrete task plan (possibly with concurrency) with a cost less than a specified value, and transform this plan into a continuous collision-free trajectory