Dynamic whole-body motion generation under rigid contacts and other unilateral constraints

The most widely used technique for generating wholebody motions on a humanoid robot accounting for various tasks and constraints is inverse kinematics. Based on the task-function approach, this class of methods enables the coordination of robot movements to execute several tasks in parallel and account for the sensor feedback in real time, thanks to the low computation cost. To some extent, it also enables us to deal with some of the robot constraints (e.g., joint limits or visibility) and manage the quasi-static balance of the robot. In order to fully use the whole range of possible motions, this paper proposes extending the task-function approach to handle the full dynamics of the robot multibody along with any constraint written as equality or inequality of the state and control variables. The definition of multiple objectives is made possible by ordering them inside a strict hierarchy. Several models of contact with the environment can be implemented in the framework. We propose a reduced formulation of the multiple rigid planar contact that keeps a low computation cost. The efficiency of this approach is illustrated by presenting several multicontact dynamic motions in simulation and on the real HRP-2 robot

Modeling and control of an anthropomorphic robotic hand

Mención Europea en el título de doctorThis thesis presents methods and tools for enabling the successful use of robotic hands. For highly dexterous and/or anthropomorphic robotic hands, these methods have to share some common goals, such as overcoming the potential complexity of the mechanical design and the ability of performing accurate tasks with low and efficient computational cost. A prerequisite for dexterity is to increase the workspace of the robotic hand. For this purpose, the robotic hand must be considered as a single multibody system. Solving the inverse kinematics problem of the whole robotic hand is an arduous task due to the high number of degrees of freedom involved and the possible mechanical limitations, singularities and other possible constraints. The redundancy has proven to be of a great usefulness for dealing with potential constraints. To be able to exploit the redundancy for dealing with constraints, the adopted method for solving the inverse kinematics must be robust and extendable. Obviously, addressing such complex problem, the method will certainly be computationally heavy. Thus, one of the aims of this thesis is to resolve the inverse kinematics problem of the whole robotic hand under constraints, taking into account the computational cost. To this end, this thesis extends and reduces the most recent Selectively Damped Least Squares method which is based on the computation of all singular values, to deal with constraints with a minimum computational cost. New estimation algorithm of singular values and their corresponding singular vectors is proposed to reduce the computational cost. The reduced extended selectively damped least squares method is simulated and experimentally evaluated using an anthropomorphic robotic hand as a test bed. On the other hand, dexterity depends not only on the accuracy of the position control, but also on the exerted forces. The tendon driven modern robotic hands, like the one used in this work, are strongly nonlinear dynamic systems, where motions and forces are transmitted remotely to the finger joints. The problem of modeling and control of position and force simultaneously at low level control is then considered. A new hybrid control structure based on the succession of two sliding mode controllers is proposed. The force is controlled by its own controller which does not need a contact model. The performance of the proposed controller is evaluated by performing the force control directly using the force sensor information of the fingertip, and indirectly using the torque control of the actuator. Finally, we expect that the applications of the methods presented in this thesis can be extended to cover different issues and research fields and in particular they can be used in a variety of algorithm that require the estimation of singular values.This work was partially supported by the European project HANDLE, FP7-231640, and by the Spanish ministry MICINN through FPI scholarship within the project DPI-2005-04302.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Anis Sahbani.- Secretario: Fares Jawad Moh D Abu-Dakka.- Vocal: Claudio Ross

Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas

The main interest of this thesis consists of the study and implementation of postprocessors to adapt the toolpath generated by a Computer Aided Manufacturing (CAM) system to a complex robotic workcell of eight joints, devoted to the rapid prototyping of 3D CAD-defined products. It consists of a 6R industrial manipulator mounted on a linear track and synchronized with a rotary table. To accomplish this main objective, previous work is required. Each task carried out entails a methodology, objective and partial results that complement each other, namely: - It is described the architecture of the workcell in depth, at both displacement and joint-rate levels, for both direct and inverse resolutions. The conditioning of the Jacobian matrix is described as kinetostatic performance index to evaluate the vicinity to singular postures. These ones are analysed from a geometric point of view. - Prior to any machining, the additional external joints require a calibration done in situ, usually in an industrial environment. A novel Non-contact Planar Constraint Calibration method is developed to estimate the external joints configuration parameters by means of a laser displacement sensor. - A first control is originally done by means of a fuzzy inference engine at the displacement level, which is integrated within the postprocessor of the CAM software. - Several Redundancy Resolution Schemes (RRS) at the joint-rate level are compared for the configuration of the postprocessor, dealing not only with the additional joints (intrinsic redundancy) but also with the redundancy due to the symmetry on the milling tool (functional redundancy). - The use of these schemes is optimized by adjusting two performance criterion vectors related to both singularity avoidance and maintenance of a preferred reference posture, as secondary tasks to be done during the path tracking. Two innovative fuzzy inference engines actively adjust the weight of each joint in these tasks.Andrés De La Esperanza, FJ. (2011). Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10627Palanci

Application of hand-eye coordination in reaching with a humanoid

Reaching is the prerequisite for all kinds of physical manipulation by which robots interact with the physical world. In this research project, we try to build an application on the iCub humanoid platform to reach visually seen objects located in workspace. We also investigate humans’ ability to reach to objects using visual feedback and intend for the application to reproduce human-like behavior with a simplified model. This application includes fine motor control, object recognition, spatial transformations, stereovision, gaze control, and hand-eye coordination. We also discuss different methods in both vision and control that we use in the application.Ope

Scaled Autonomy for Networked Humanoids

Humanoid robots have been developed with the intention of aiding in environments designed for humans. As such, the control of humanoid morphology and effectiveness of human robot interaction form the two principal research issues for deploying these robots in the real world. In this thesis work, the issue of humanoid control is coupled with human robot interaction under the framework of scaled autonomy, where the human and robot exchange levels of control depending on the environment and task at hand. This scaled autonomy is approached with control algorithms for reactive stabilization of human commands and planned trajectories that encode semantically meaningful motion preferences in a sequential convex optimization framework. The control and planning algorithms have been extensively tested in the field for robustness and system verification. The RoboCup competition provides a benchmark competition for autonomous agents that are trained with a human supervisor. The kid-sized and adult-sized humanoid robots coordinate over a noisy network in a known environment with adversarial opponents, and the software and routines in this work allowed for five consecutive championships. Furthermore, the motion planning and user interfaces developed in the work have been tested in the noisy network of the DARPA Robotics Challenge (DRC) Trials and Finals in an unknown environment. Overall, the ability to extend simplified locomotion models to aid in semi-autonomous manipulation allows untrained humans to operate complex, high dimensional robots. This represents another step in the path to deploying humanoids in the real world, based on the low dimensional motion abstractions and proven performance in real world tasks like RoboCup and the DRC

Robotic manipulation for the shoe-packaging process

[EN] This paper presents the integration of a robotic system in a human-centered environment, as it can be found in the shoe manufacturing industry. Fashion footwear is nowadays mainly handcrafted due to the big amount of small production tasks. Therefore, the introduction of intelligent robotic systems in this industry may contribute to automate and improve the manual production steps, such us polishing, cleaning, packaging, and visual inspection. Due to the high complexity of the manual tasks in shoe production, cooperative robotic systems (which can work in collaboration with humans) are required. Thus, the focus of the robot lays on grasping, collision detection, and avoidance, as well as on considering the human intervention to supervise the work being performed. For this research, the robot has been equipped with a Kinect camera and a wrist force/ torque sensor so that it is able to detect human interaction and the dynamic environment in order to modify the robot¿s behavior. To illustrate the applicability of the proposed approach, this work presents the experimental results obtained for two actual platforms, which are located at different research laboratories, that share similarities in their morphology, sensor equipment and actuation system.This work has been partly supported by the Ministerio de Economia y Competitividad of the Spanish Government (Key No.: 0201603139 of Invest in Spain program and Grant No. RTC-2016-5408-6) and by the Deutscher Akademischer Austauschdienst (DAAD) of the German Government (Projekt-ID 54368155).Gracia Calandin, LI.; Perez-Vidal, C.; Mronga, D.; Paco, JD.; Azorin, J.; Gea, JD. (2017). Robotic manipulation for the shoe-packaging process. The International Journal of Advanced Manufacturing Technology. 92(1-4):1053-1067. https://doi.org/10.1007/s00170-017-0212-6S10531067921-4Pedrocchi N, Villagrossi E, Cenati C, Tosatti LM (2017) Design of fuzzy logic controller of industrial robot for roughing the uppers of fashion shoes. Int J Adv Manuf Technol 77(5):939–953Hinojo-Perez JJ, Davia-Aracil M, Jimeno-Morenilla A, Sanchez-Romero L, Salas F (2016) Automation of the shoe last grading process according to international sizing systems. Int J Adv Manuf Technol 85(1):455–467Dura-Gil JV, Ballester-Fernandez A, Cavallaro M, Chiodi A, Ballarino A, von Arnim V., Brondi C, Stellmach D (2016) New technologies for customizing products for people with special necessities: project fashion-able. Int J Comput Integr Manuf. In Press, doi: 10.1080/0951192X.2016.1145803Jatta F, Zanoni L, Fassi I, Negri S (2004) A roughing/cementing robotic cell for custom made shoe manufacture. Int J Comput Integr Manuf 17(7):645–652Nemec B, Zlajpah L (2008) Robotic cell for custom finishing operations. Int J Comput Integr Manuf 21(1):33–42Molfino R, et al (2004) Modular, reconfigurable prehensor for grasping and handling limp materials in the shoe industry. In: IMS international forum, CernobbioIntelishoe - integration and linking of shoe and auxiliary industries. 5Th FPSpecial shoes movement. 7th FP, NMP-2008-SME-2-R.229261, http://www.sshoes.euVilaca JL, Fonseca J (2007) A new software application for footwear industry. In: IEEE international symposium on intelligent signal processing WISP 2007, pp 1–6Custom, environment and comfort made shoe. 6TH FP [2004-2008]Framework of integrated technologies for user centred products. Grant agreement no.: CP-TP 229336-2. NMP2-SE-2009-229336 FIT4U -7TH FPRobofoot project website. http://www.robofoot.eu/ . Accessed 2016/ 09/16Montiel E (2007) Customization in the footwear industry. In: proceedings of the MIT congress on mass customizationSucan I, Kavraki LE (2012) A sampling-based tree planner for systems with complex dynamics, vol 28Kuffner JJ Jr, LaValle SM (2000) Rrt-connect: an efficient approach to single-query path planning. In: Proceedings of the IEEE international conference on robotics and automation, 2000. ICRA ’00, vol 2, pp 995–1001Ratliff N, Zucker M, Andrew Bagnell J, Srinivasa S (2009) Chomp: gradient optimization techniques for efficient motion planning. In: IEEE international conference on robotics and automation, 2009. ICRA ’09, pp 489–494Brock O, Khatib O (1997) Elastic strips: real-time path modification for mobile manipulationKroger T (2011) Opening the door to new sensor-based robot applications #x2014;the reflexxes motion libraries. In: 2011 IEEE international conference on robotics and automation (ICRA), pp 1–4Berg J, Ferguson D, Kuffner J (2006) Anytime path planning and replanning in dynamic environments. In: Proceedings of the IEEE international conference on robotics and automation (ICRA), pp 2366–2371Berenson D, Abbeel P, Goldberg K (2012) A robot path planning framework that learns from experience. In: IEEE international conference on robotics and automation. IEEE, pp 3671–3678Bischoff R, Kurth J, Schreiber G, Koeppe R, Albu-Schaeffer A, Beyer A, Eiberger O, Haddadin S, Stemmer A, Grunwald G, Hirzinger G (2010) The kuka-dlr lightweight robot arm — a new reference platform for robotics research and manufacturing. In: Robotics (ISR), 2010 41st international symposium on and 2010 6th German conference on robotics (ROBOTIK), pp 1–8Rooks B (2006) The harmonious robot. Industrial Robot-an International Journal 33:125–130Vahrenkamp N, Wieland S, Azad P, Gonzalez D, Asfour T, Dillmann R (2008) Visual servoing for humanoid grasping and manipulation tasks. In: 8th IEEE-RAS international conference on humanoid robots, 2008, Humanoids 2008, pp 406–412Pieters RS, et al. (2012) Direct trajectory generation for vision-based obstacle avoidance. In: Proceedings of the 2012 IEEE/RSJ international conference on intelligent robots and systemsKinect for windows sensor components and specifications, website. http://msdn.microsoft.com/en-us/library/jj131033.aspx . Accessed 2016/09/16Jatta F, Zanoni L, Fassi I, Negri S (2004) A roughing cementing robotic cell for custom made shoe manufacture. Int J Comput Integr Manuf 17(7):645–652Maurtua I, Ibarguren A, Tellaeche A (2012) Robotics for the benefit of footwear industry. In: International conference on intelligent robotics and applications. Springer, Berlin, pp 235–244Arkin RC (1998) Behavior-based robotics. MIT PressNilsson NJ (1980) Principles of artificial intelligence. Morgan KaufmannAsada H, Slotine J-JE (1986) Robot analysis and control. WileyROS official web page. http://www.ros.org , (Accessed on 2017/ 02/03)Langmann B, Hartmann K, Loffeld O (2012) Depth camera technology comparison and performance evaluation. In: 1st international conference on pattern recognition applications and methods, pp 438–444The player project. free software tools for robot and sensor applications. http://playerstage.sourceforge.net/ , (Accessed on 2017/ 02/03)Yet another robot platform (YARP). http://www.yarp.it/ , (Accessed on 2017/02/03)The OROCOS project. smarter control in robotics and automation. http://www.orocos.org/ , (Accessed on 2017/02/03)CARMEN: Robot navigation toolkit. http://carmen.sourceforge.net/ , (Accessed on 2017/02/03)ORCA: Components for robotics. http://orca-robotics.sourceforge.net/ , (Accessed on 2017/02/03)MOOS: Mission oriented operating suite. http://www.robots.ox.ac.uk/mobile/MOOS/wiki/pmwiki.php/Main/HomePage , (Accessed on 2017/02/03)Microsoft robotics studio. https://www.microsoft.com/en-us/download/details.aspx?id=29081 , (Accessed on 2017/02/03)Pr2 ros website. http://www.ros.org/wiki/Robots/PR2 . Accessed 2016/09/16Care-o-bot 3 ros website. http://www.ros.org/wiki/Robots/Care-O-bot . Accessed 2016/09/16Aila, mobile dual-arm manipulation, website. http://robotik.dfki-bremen.de/de/forschung/robotersysteme/aila.html . Accessed 2016/09/16Package libpcan documentation, website. http://www.ros.org/wiki/libpcan . Accessed 2016/09/16Pcan driver for linux, user manual. http://www.peak-system.com . Document version 7.1 (2011-03-21)Pcan driver for linux, user manual. http://wiki.ros.org/schunk_powercube_chain . Accessed 2016/09/16Ros nodes documentation, website. http://www.ros.org/wiki/Nodes . Accessed 2016/09/16Ros messages documentation, website. http://www.ros.org/wiki/Messages . Accessed 2016/09/16Ros topics documentation, website. http://www.ros.org/wiki/Topics . Accessed 2016/09/16Ros services documentation, website. http://www.ros.org/wiki/Services . Accessed 2016/09/16Yaml files officials website. http://www.yaml.org/ . Accessed 2016/ 09/16Ros robot model (urdf) documentation website. http://www.ros.org/wiki/urdf . Accessed 2016/09/16Point cloud library (pcl), website. http://www.pointclouds.org/ . Accessed 2016/09/16Arm navigation ros stack, website. http://wiki.ros.org/arm_navigation . Accessed 2016/09/16Hornung A, Wurm KM, Bennewitz M, Stachniss C, Burgard W (2013) Octomap: an efficient probabilistic 3d mapping framework based on octrees Autonomous RobotsOrocos kdl documentation, website. http://www.orocos.org/kdl . Accessed 2016/09/16Ioan A, Şucan MM, Kavraki LE (2012) The open motion planning library, vol 19. http://ompl.kavrakilab.orgWaibel M, Beetz M, Civera J, D’Andrea R, Elfring J, Galvez-Lopez D, Haussermann K, Janssen R, Montiel JMM, Perzylo A, Schiessle B, Tenorth M, Zweigle O, van de Molengraft R (2011) Roboearth. IEEE Robot Autom Mag 18(2):69–82Simox toolbox. http://simox.sourceforge.net/ . Accessed 2016/09/16Moreels P, Perona P (2007) Evaluation of features detectors and descriptors based on 3d objects. Int J Comput Vis 73:263–284Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Proceedings of the IEEE computer society conference on computer vision and pattern recognition, 2001. CVPR 2001, vol 1Teuliere C, Marchand E, Eck L (2010) Using multiple hypothesis in model-based tracking. In: 2010 IEEE international conference on robotics and automation (ICRA), pp 4559–4565Moulianitis VC, Dentsoras AJ, Aspragathos NA (1999) A knowledge-based system for the conceptual design of grippers for handling fabrics. Artif Intell Eng Des Anal Manuf 13(1):13–25Davis S, Tsagarakis NG, Caldwell DG (2008) The initial design and manufacturing process of a low cost hand for the robot icub. In: 8th IEEE-RAS international conference on humanoid robots, pp 40–45Cerruti G, Chablat D, Gouaillier D, Sakka S (2017) Design method for an anthropomorphic hand able to gesture and grasp. In: IEEE international conference on robotics and automation. IEEE, pp 3671–367

Collaborative mobile industrial manipulator : a review of system architecture and applications

This paper provides a comprehensive review of the development of Collaborative Mobile Industrial Manipulator (CMIM), which is currently in high demand. Such a review is necessary to have an overall understanding about CMIM advanced technology. This is the first review to combine the system architecture and application which is necessary in order to gain a full understanding of the system. The classical framework of CMIM is firstly discussed, including hardware and software. Subsystems that are typically involved in hardware such as mobile platform, manipulator, end-effector and sensors are presented. With regards to software, planner, controller, perception, interaction and so on are also described. Following this, the common applications (logistics, manufacturing and assembly) in industry are surveyed. Finally, the trends are predicted and issues are indicated as references for CMIM researchers. Specifically, more research is needed in the areas of interaction, fully autonomous control, coordination and standards. Besides, experiments in real environment would be performed more and novel collaborative robotic systems would be proposed in future. Additionally, some advanced technology in other areas would also be applied into the system. In all, the system would become more intelligent, collaborative and autonomous

Proceedings of the 3rd Annual Conference on Aerospace Computational Control, volume 1

Conference topics included definition of tool requirements, advanced multibody component representation descriptions, model reduction, parallel computation, real time simulation, control design and analysis software, user interface issues, testing and verification, and applications to spacecraft, robotics, and aircraft

Robot Assisted Object Manipulation for Minimally Invasive Surgery

Robotic systems have an increasingly important role in facilitating minimally invasive surgical treatments. In robot-assisted minimally invasive surgery, surgeons remotely control instruments from a console to perform operations inside the patient. However, despite the advanced technological status of surgical robots, fully autonomous systems, with decision-making capabilities, are not yet available. In 2017, a structure to classify the research efforts toward autonomy achievable with surgical robots was proposed by Yang et al. Six different levels were identified: no autonomy, robot assistance, task autonomy, conditional autonomy, high autonomy, and full autonomy. All the commercially available platforms in robot-assisted surgery is still in level 0 (no autonomy). Despite increasing the level of autonomy remains an open challenge, its adoption could potentially introduce multiple benefits, such as decreasing surgeons’ workload and fatigue and pursuing a consistent quality of procedures. Ultimately, allowing the surgeons to interpret the ample and intelligent information from the system will enhance the surgical outcome and positively reflect both on patients and society. Three main aspects are required to introduce automation into surgery: the surgical robot must move with high precision, have motion planning capabilities and understand the surgical scene. Besides these main factors, depending on the type of surgery, there could be other aspects that might play a fundamental role, to name some compliance, stiffness, etc. This thesis addresses three technological challenges encountered when trying to achieve the aforementioned goals, in the specific case of robot-object interaction. First, how to overcome the inaccuracy of cable-driven systems when executing fine and precise movements. Second, planning different tasks in dynamically changing environments. Lastly, how the understanding of a surgical scene can be used to solve more than one manipulation task. To address the first challenge, a control scheme relying on accurate calibration is implemented to execute the pick-up of a surgical needle. Regarding the planning of surgical tasks, two approaches are explored: one is learning from demonstration to pick and place a surgical object, and the second is using a gradient-based approach to trigger a smoother object repositioning phase during intraoperative procedures. Finally, to improve scene understanding, this thesis focuses on developing a simulation environment where multiple tasks can be learned based on the surgical scene and then transferred to the real robot. Experiments proved that automation of the pick and place task of different surgical objects is possible. The robot was successfully able to autonomously pick up a suturing needle, position a surgical device for intraoperative ultrasound scanning and manipulate soft tissue for intraoperative organ retraction. Despite automation of surgical subtasks has been demonstrated in this work, several challenges remain open, such as the capabilities of the generated algorithm to generalise over different environment conditions and different patients