A Resilient and Effective Task Scheduling Approach for Industrial Human-Robot Collaboration.

Effective task scheduling in human-robot collaboration (HRC) scenarios is one of the great challenges of collaborative robotics. The shared workspace inside an industrial setting brings a lot of uncertainties that cannot be foreseen. A prior offline task scheduling strategy is ineffective in dealing with these uncertainties. In this paper, a novel online framework to achieve a resilient and reliable task schedule is presented. The framework can deal with deviations that occur during operation, different operator skills, error by the human or robot, and substitution of actors, while maintaining an efficient schedule by promoting parallel human-robot work. First, the collaborative job and the possible deviations are represented by AND/OR graphs. Subsequently, the proposed architecture chooses the most suitable path to improve the collaboration. If some failures occur, the AND/OR graph is adapted locally, allowing the collaboration to be completed. The framework is validated in an industrial assembly scenario with a Franka Emika Panda collaborative robot.

Feasibility of a telementoring approach as a practical training for transurethral enucleation of the benign prostatic hyperplasia using bipolar energy: a pilot study.

INTRODUCTION: Telementoring is one of the applications of telemedicine capable of bringing highly experienced surgeons to areas lacking expertise. In the current study, we aimed to assess a novel telementoring application during the learning curve of transurethral enucleation of the prostate using bipolar energy (TUEB). MATERIAL AND METHODS: A telementoring system was developed by our engineering department. This application was used to mentor ten prospective cases of TUEB performed by an expert endourologist (novice to the TUEB). A questionnaire was filled by the operating surgeon and the mentor to provide subjective evaluation of the telementoring system. Finally, the outcomes of these patients were compared to a control group consisting of ten consecutive patients performed by the mentor. RESULTS: Ten consecutive TUEB were performed using this telementoring application. Delayed and interrupted connection were experienced in two and one patients, respectively; however, their effect was minor, and they did not compromise the safety of the procedure. None of the patients required conversion to conventional transurethral resection of the prostate. Only one patient in our series experienced grade IIIb complication. CONCLUSION: The telementoring application for TUEB is promising. It is a simple and low-cost tool that could be a feasible option to ensure patients' safety during the initial phase of the learning curve without time and locations constraints for both the mentor and the trainee; However, it should be mentioned that telementoring cannot yet replace the traditional surgical training with the mentor and trainee being in the operative room. Further studies are required to confirm the current results.

Coordinated Dynamic Behaviors for Multirobot Systems With Collision Avoidance.

In this paper, we propose a novel methodology for achieving complex dynamic behaviors in multirobot systems. In particular, we consider a multirobot system partitioned into two subgroups: 1) dependent and 2) independent robots. Independent robots are utilized as a control input, and their motion is controlled in such a way that the dependent robots solve a tracking problem, that is following arbitrarily defined setpoint trajectories, in a coordinated manner. The control strategy proposed in this paper explicitly addresses the collision avoidance problem, utilizing a null space-based behavioral approach: this leads to combining, in a non conflicting manner, the tracking control law with a collision avoidance strategy. The combination of these control actions allows the robots to execute their task in a safe way. Avoidance of collisions is formally proven in this paper, and the proposed methodology is validated by means of simulations and experiments on real robots.

Decentralized Estimation and Control for Preserving the Strong Connectivity of Directed Graphs.

In order to accomplish cooperative tasks, decentralized systems are required to communicate among each other. Thus, maintaining the connectivity of the communication graph is a fundamental issue. Connectivity maintenance has been extensively studied in the last few years, but generally considering undirected communication graphs. In this paper, we introduce a decentralized control and estimation strategy to maintain the strong connectivity property of directed communication graphs. In particular, we introduce a hierarchical estimation procedure that implements power iteration in a decentralized manner, exploiting an algorithm for balancing strongly connected directed graphs. The output of the estimation system is then utilized for guaranteeing preservation of the strong connectivity property. The control strategy is validated by means of analytical proofs and simulation results.

An algorithm for planning the number and the pose of the iceballs in cryoablation.

We present an algorithm that computes the number and the pose (position and orientation) of iceballs in a cryoablation procedure, in order to completely cover the target region, i.e. the tumor. Constraints to needle insertion, such as regions that have to be avoided, are taken into account and satisfied. We developed a tool for cryosurgery planning in MATLAB and perform several simulations to extract information on the algorithm behavior and to verify that it always brings to a complete coverage.