Nonlinear Control and Estimation
One of the main research streams in our group is developing modern model-based nonlinear estimation and control methods for complex dynamical systems in a wide range of applications, from robotics and autonomous vehicles to aerospace engineering. They also allow for making more accurate predictions about the system behavior, as well as designing optimal and robust controllers that can adapt quickly when faced with unexpected changes, disturbances, or uncertainties of the real-world.
Contributions
As a fundamental basis for the sensitivity of robots, we have developed several disturbance observer based methods for accurate and high-bandwidth collision handling, reflex reaction [69, 70, 71, 72] and fault detection in manipulators [73, 74] and humanoids [75], or simultaneous contact and wind estimation in flying systems [77, 78, 79, 80]. Variants include the observer-extended direct method or the model-adaptive high-speed collision detection framework [70, 81]. Moreover, new calibration algorithms were derived, which outperformed conventional techniques and enhanced the robot model for the identification process [73]. In addition, we developed novel techniques for designing nonlinear observers and state estimators for accurate joint velocity and acceleration based on joint position and IMU measurements [45, 82].
Concerning energy-aware interaction control, our research aims to equip robots with soft, force-sensitive, and inherently safe behavior via elegantly designed controllers. Among others, our group’s contributions include unified force/ impedance control (UFIC) [84, 85], UFIC for multi-robot systems [86], or bio-inspired, adaptive controllers for force-sensitive robots [88].
Our developments in rehabilitation control algorithms that adapt to the individual human ability and rehabilitation goals (e.g. assist as needed [68]) integrate model-based compliant control approaches with human neuromusculoskeletal models and learning algorithms [90]. Our group’s contributions to optimal control of elastic robots with particular focus on maximum dynamic performance at minimum energy consumption are early examples of exploiting inherent dynamics in manipulation [9, 46, 91, 92, 93, 94, 95, 97, 98, 99], including also novel controllers for dynamic manipulation such as blind dribbling [47]. We leveraged these fundamental findings in designing novel actuators such as the Bi-Stiffness Actuator, where we investigate methods to optimally exploit intrinsic elasticity as well as inertial coupling effects enabled by clutching [100]. We also introduced optimization and MPC-based planning and control policies for dynamic manipulation for complex manipulation like no-spill tasks [102]. Distributed and networked control are powerful tools for multi-robot systems, telepresence and recently for coordinated control [103]. We introduced a telepresence reference platform based on state-of-the-art robot systems for evaluating the impact of wireless communication protocols on telepresence systems. We provided the first comparative analysis on 5G, LTE, and WiFi communication protocols on motion and force-tracking performance [104].
Based on exhaustive industrial tactile task analysis, we introduced novel performance benchmarking and testing metrics that characterize and quantify a robot’s ability to physically interact and manipulate [106]. This also includes the safety abilities for which we introduced the contact sensitivity map (CSM) [107], or the guidance performance [108]. We applied these tactile interaction metrics to experimentally benchmark all relevant industrial robot systems of the next generation [106], unveiling also a natural classification surface between robot generations.
[9] Sami Haddadin, Mehmet Can Özparpucu, and Alin Albu-Schäffer. “Optimal control for maximizing potential energy in a variable stiffness joint”. In: IEEE Conference on Decision and Control (CDC). 2012, pp. 1199–1206.
[45] Seyed Ali Baradaran Birjandi, Niels Dehio, Abderrahmane Kheddar, and Sami Haddadin. “Robust Cartesian Kinematics Estimation for Task-Space Control Systems”. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2022, pp. 3512–3519.
[46] Sami Haddadin, Felix Huber, and Alin Albu-Schäffer. “Optimal control for exploiting the natural dynamics of variable stiffness robots”. In: Robotics and Automation (ICRA), 2012 IEEE International Conference on. IEEE. 2012, pp. 3347–3354.
[47] Sami Haddadin, Kai Krieger, and Alin Albu-Schäffer. “Exploiting elastic energy storage for cyclic manipulation: Modeling, stability, and observations for dribbling”. In: Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on. Dec. 2011, pp. 690– 697.
[68] Kim K. Peper, Dinmukhamed Zardykhan, Marion Egger, Martina Steinböck, Friedemann Müller, Xavier Hildenbrand, Alexander Koenig, Elisabeth R. Jensen, and Sami Haddadin. “Testing RobotBased Assist-as-Needed Therapy for Improving Active Participation of a Patient during Early Neurorehabilitation: A Case Study”. In: 2022 International Conference on Rehabilitation Robotics (ICORR). Rotterdam, Netherlands: IEEE Press, 2022, pp. 1–6.
[69] Alessandro De Luca, Alin Albu-Schäffer, Sami Haddadin, and Gerd Hirzinger. “Collision detection and safe reaction with the DLR-III lightweight manipulator arm”. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2006, pp. 1623–1630.
[70] Seyed Ali Baradaran Birjandi, Johannes Kühn, and Sami Haddadin. “Observer-Extended Direct Method for Collision Monitoring in Robot Manipulators Using Proprioception and IMU Sensing”. In: IEEE Robotics and Automation Letters 5.2 (2020), pp. 954–961.
[71] Sami Haddadin, Alin Albu-Schäffer, Alessandro De Luca, and Gerd Hirzinger. “Collision detection and reaction: A contribution to safe physical human-robot interaction”. In: Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on. IEEE. 2008, pp. 3356– 3363.
[72] Sami Haddadin, Alin Albu-Schäffer, Alessandro De Luca, and Gerd Hirzinger. “Evaluation of collision detection and reaction for a human-friendly robot on biological tissues”. In: 6th IARP/IEEE/EURON Joint Workshop on Technical Challenges for Dependable Robots in Human Environments (IARP2008). Pasadena, USA, 2008.
[73] Alexander Kurdas, Mazin Hamad, Jonathan Vorndamme, Nico Mansfeld, Saeed Abdolshah, and Sami Haddadin. “Online Payload Identification for Tactile Robots Using the Momentum Observer”. In: 2022 International Conference on Robotics and Automation (ICRA). IEEE. 2022, pp. 5953–5959.
[74] Jonathan Vorndamme, Luis Figueredo, and Sami Haddadin. “Robot Contact Reflexes: Adaptive Maneuvers in the Contact Reflex Space”. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2022, pp. 6687–6694.
[75] Johannes Kuehn and Sami Haddadin. “An Artificial Robot Nervous System To Teach Robots How To Feel Pain And Reflexively React To Potentially Damaging Contacts”. In: IEEE Robotics and Automation Letters 2.1 (Jan. 2017), pp. 72–79.
[77] Teodor Tomic, Christian Ott, and Sami Haddadin. “External Wrench Estimation, Collision Detection, and Reflex Reaction for Flying Robots”. In: IEEE Transactions on Robotics 33.6 (2017), pp. 1467–1482.
[78] Teodor Tomic and Sami Haddadin. “A unified framework for external wrench estimation, interaction control and collision reflexes for flying robots”. In: Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on. Sept. 2014, pp. 4197–4204.
[79] Teodor Tomic and Sami Haddadin. “Towards interaction, disturbance and fault aware flying robot ´ swarms”. In: Robotics Research. Springer, 2020, pp. 183–198.
[80] Alexander Moortgat-Pick, Anna Adamczyk, Teodor Tomic, and Sami Haddadin. “Feeling the ´ True Force in Haptic Telepresence for Flying Robots”. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2020, pp. 9789–9796.
[81] Seyed Ali Baradaran Birjandi and Sami Haddadin. “Model-Adaptive High-Speed Collision Detection for Serial-Chain Robot Manipulators”. In: IEEE Robotics and Automation Letters 5.4 (2020), pp. 6544–6551.
[82] Seyed Ali Baradaran Birjandi, Johannes Kühn, and Sami Haddadin. “Joint Velocity and Acceleration Estimation in Serial Chain Rigid Body and Flexible Joint Manipulators”. In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2019, pp. 7503–7509.
[84] Christopher Schindlbeck and Sami Haddadin. “Unified passivity-based cartesian force/impedance control for rigid and flexible joint robots via task-energy tanks”. In: IEEE International Conference on Robotics and Automation (ICRA). 2015, pp. 440–447.
[85] Alexander Toedtheide, Erfan Shahriari, and Sami Haddadin. “Tank based unified torque/impedance control for a pneumatically actuated antagonistic robot joint”. In: 2017 IEEE International Conference on Robotics and Automation (ICRA). May 2017, pp. 1255–1262.
[86] Erfan Shahriari, Seyed Ali Baradaran Birjandi, and Sami Haddadin. “Passivity-Based Adaptive Force-Impedance Control for Modular Multi-Manual Object Manipulation”. In: IEEE Robotics and Automation Letters 7.2 (2022), pp. 2194–2201.
[88] Kübra Karacan, Hamid Sadeghian, Robin Kirschner, and Sami Haddadin. “Passivity-Based Skill Motion Learning in Stiffness-Adaptive Unified Force-Impedance Control”. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2022, pp. 9604–9611.
[90] Nicolas Seppich, Nicholas Tacca, Kuo-Yi Chao, Milan Akim, Diego Hidalgo-Carvajal, Edmundo Pozo Fortunic, Alexander Tödtheide, Johannes Kühn, and Sami Haddadin. “CyberLimb: a novel ´ robotic prosthesis concept with shared and intuitive control”. In: Journal of NeuroEngineering and Rehabilitation 19.1 (2022), pp. 1–20.
[91] Mehmet Can Özparpucu, Sami Haddadin, and Alin Albu-Schäffer. “Optimal control of variable stiffness actuators with nonlinear springs”. In: World Congress of the International Federation of Automatic Control 47.3 (2014), pp. 8487–8495.
[92] Mehmet Can Özparpucu and Sami Haddadin. “Optimal control for maximizing link velocity of visco-elastic joints”. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2013, pp. 3035–3042.
[93] Mehmet Can Özparpucu and Sami Haddadin. “Optimal control of elastic joints with variable damping”. In: European Control Conference (ECC). 2014, pp. 2526–2533.
[94] Can Mehmet Özparpucu, Sami Haddadin, and Alin Albu-Schäffer. “Optimal Control of Variable Stiffness Actuators with Nonlinear Springs”. In: 19th IFAC World Congress. Cape Town, South Africa, Aug. 2014, pp. 8487–8495.
[95] Can Mehmet Özparpucu and Sami Haddadin. “Optimal control of elastic joints with variable damping”. In: Control Conference (ECC), 2014 European. Strasbourg, France, June 2014, pp. 2526–2533.
[97] Sami Haddadin, Michael Weis, Sebastian Wolf, and Alin Albu-Schäffer. “Optimal control for maximizing link velocity of robotic variable stiffness joints”. In: World Congress of the International Federation of Automatic Control 44.1 (2011), pp. 6863–6871.
[98] Sami Haddadin, Roman Weitschat, Felix Huber, Mehmet Can Özparpucu, Nico Mansfeld, and Alin Albu-Schäffer. “Optimal control for viscoelastic robots and its generalization in real-time”. In: Robotics Research. Springer, 2016, pp. 131–148.
[99] Can Mehmet Özparpucu and Sami Haddadin. “Optimal control for maximizing link velocity of visco-elastic joints”. In: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on. IEEE. 2013, pp. 3035–3042.
[100] Dennis Ossadnik, Mehmet C. Yildirim, Fan Wu, Abdalla Swikir, Hugo T. M. Kussaba, Saeed Abdolshah, and Sami Haddadin. “BSA - Bi-Stiffness Actuation for optimally exploiting intrinsic compliance and inertial coupling effects in elastic joint robots”. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2022, pp. 3536–3543.
[102] Rafael I. Cabral Muchacho, Riddhiman Laha, Luis F.C. Figueredo, and Sami Haddadin. “A Solution to Slosh-free Robot Trajectory Optimization”. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2022, pp. 223–230.
[103] Lingyun Chen, Abdalla Swikir, and Sami Haddadin. “Drawing Elon Musk: A Robot Avatar for Remote Manipulation”. In: 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2021, pp. 4244–4251.
[104] Xiao Chen, Lars Johannsmeier, Hamid Sadeghian, Erfan Shahriari, Martin Danneberg, Anselm Nicklas, Fan Wu, Gerhard Fettweis, and Sami Haddadin. “On the Communication Channel in Bilateral Teleoperation: An Experimental Study for Ethernet, WiFi, LTE and 5G”. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2022, pp. 7712– 7719.
[106] Robin Jeanne Kirschner, Alexander Kurdas, Kübra Karacan, Philipp Junge, Seyed Ali Baradaran Birjandi, Nico Mansfeld, Saeed Abdolshah, and Sami Haddadin. “Towards a Reference Framework for Tactile Robot Performance and Safety Benchmarking”. In: 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2021, pp. 4290–4297.
[107] Robin Jeanne Kirschner, João Jantalia, Nico Mansfeld, Saeed Abdolshah, and Sami Haddadin. “CSM: Contact Sensitivity Maps for Benchmarking Robot Collision Handling Systems”. In: 2021 IEEE International Conference on Robotics and Automation (ICRA). 2021, pp. 3590–3596.
[108] Robin Jeanne Kirschner, Florian Martineau, Nico Mansfeld, Saeed Abdolshah, and Sami Haddadin. “Manual Maneuverability: Metrics for Analysing and Benchmarking Kinesthetic Robot Guidance”. In: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2022, pp. 13414–13421.