Passivity and Stability of Human–Robot Interaction Control for Upper-Limb Rehabilitation Robots
TL;DR: A theoretical framework is presented that establishes the passivity of the closed-loop upper-limb rehabilitative robotic systems and allows rigorous stability analysis of human-robot interaction and realizes the “assist-as-needed” strategy.
Abstract: Each year, stroke and traumatic brain injury leave millions of survivors with motion control loss, which results in great demand for recovery training. The great labor intensity in traditional human-based therapies has recently boosted the research on rehabilitation robotics. Existing controllers for rehabilitative robotics cannot solve the closed-loop system stability with uncertain nonlinear dynamics and conflicting human–robot interactions. This paper presents a theoretical framework that establishes the passivity of the closed-loop upper-limb rehabilitative robotic systems and allows rigorous stability analysis of human–robot interaction. Position-dependent stiffness and position-dependent desired trajectory are employed to resolve the possible conflicts in motions between patient and robot. The proposed method also realizes the “assist-as-needed” strategy. In addition, it handles human–robot interactions in such a way that correct movements are encouraged and incorrect ones are suppressed to make the training process more effective. While guaranteeing these properties, the proposed controller allows parameter adjustment to provide flexibility for therapists to adjust and fine tune depending on the conditions of the patients and the progress of their recovery. Simulation and experiment results are presented to illustrate the performance of the method.
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TL;DR: A novel continuous adaptive control method is proposed for SEA-driven robots used in human–robot interaction that provides a unified formulation for both the robot-in-charge mode, where the robot plays a dominant role to follow a desired trajectory, and the human- in-charge mode, in which the human plays a Dominant role to guide the movement of robot.
Abstract: Series elastic actuators (SEAs) are known to offer a range of advantages over stiff actuators for human-robot interaction, such as high force/torque fidelity, low impedance, and tolerance to shocks. While a variety of SEAs have been developed and implemented in initiatives that involve physical interactions with humans, relatively few control schemes were proposed to deal with the dynamic stability and uncertainties of robotic systems driven by SEAs, and the open issue of safety that resolves the conflicts of motion between the human and the robot has not been systematically addressed. In this paper, a novel continuous adaptive control method is proposed for SEA-driven robots used in human-robot interaction. The proposed method provides a unified formulation for both the robot-in-charge mode, where the robot plays a dominant role to follow a desired trajectory, and the human-in-charge mode, in which the human plays a dominant role to guide the movement of robot. Instead of designing multiple controllers and switching between them, both typical modes are integrated into a single controller, and the transition between two modes is smooth and stable. Therefore, the proposed controller is able to detect the human motion intention and guarantee the safe human-robot interaction. The dynamic stability of the closed-loop system is theoretically proven by using the Lyapunov method, with the consideration of uncertainties in both the robot dynamics and the actuator dynamics. Both simulation and experimental results are presented to illustrate the performance of the proposed controller.
143 citations
TL;DR: An iterative learning impedance controller for rehabilitation robots driven by series elastic actuators (SEAs), where the control objective is specified as a desired impedance model and the stability of the overall system is rigorously proved with Lyapunov methods by taking into account both the robot and actuator dynamics.
112 citations
Cites methods from "Passivity and Stability of Human–Ro..."
...In actual implementations, the parameters of the desired impedance model should also be initialized according to the assessment of patients’ specific conditions (Zhang & Cheah, 2015)....
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26 May 2015
TL;DR: The results indicate that model-free, integration-free feedback control is suited to the uncertain dynamics of the human-robot system, while iterative learning is effective in the cyclic task of walking.
Abstract: Few comparisons have been performed across torque controllers for exoskeletons, and differences among devices have made interpretation difficult. In this study, we designed, developed and compared the torque-tracking performance of nine control methods, including variations on classical feedback control, model-based control, adaptive control and iterative learning. Each was tested with four high-level controllers that determined desired torque based on time, joint angle, a neuromuscular model, or electromyography. Controllers were implemented on a tethered ankle exoskeleton with series elastic actuation. Measurements were taken while one human subject walked on a treadmill at 1.25 m·s−1 for one hundred steady-state steps. The combination of proportional control with damping injection and iterative learning resulted in the lowest errors for all high-level controllers. With time-based desired torque, root-mean-squared errors were 0.6 N·m (1.3% of peak desired torque) step by step, and 0.1 N·m (0.2%) on average. These results indicate that model-free, integration-free feedback control is suited to the uncertain dynamics of the human-robot system, while iterative learning is effective in the cyclic task of walking.
99 citations
Cites background from "Passivity and Stability of Human–Ro..."
...L2: Proportional Control with Damping Injection and Error-Dependent Gains (PD+EDG) This controller was the same as L1, except that the proportional gain was error-dependent [17, 18]: Kp = min[ceil( |eτ | hτ )hk,Kmax] ∆θm,des = −Kpeτ −Kdθ̇m (3)...
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TL;DR: A multi-modal control scheme for rehabilitation robotic exoskeletons that achieves the paradigm of “assist-as-needed” and also guarantees the safety of the human is presented.
Abstract: In the past few decades, a variety of rehabilitation robotic exoskeletons have been developed for patients with stroke and traumatic brain injury, which can assist therapists and potentially improv...
66 citations
Cites background or methods from "Passivity and Stability of Human–Ro..."
...However, these methods (Pehlivan et al., 2016; Wolbrecht et al., 2008; Zhang and Cheah, 2015) are developed for rigidjoint robots, and the safety measure, such as in Zhang and Cheah (2015), is dependent on the relative position between the human and the robot....
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...The transition between multiple modes is smooth and stable and also embedded into the control scheme, and hence both the objective of “AAN” and the safety of the human are guaranteed by using the regional position and force feedback....
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...Therefore, the interaction vector is capable of rejecting incorrect forces and amplifying correct forces, and the use of the interaction vector realizes the paradigm of “AAN”....
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...In parallel, much progress has been achieved in understanding the paradigm of “assist-as-needed (AAN)” for rehabilitation....
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...The concept of virtual impedance wall was proposed in Banala et al. (2009) and Duschau–Wicke et al. (2010) to realize “AAN”, by accepting and amplifying the correct movements inside the virtual wall while rejecting movements outside of it....
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TL;DR: A novel approach for intuitive and natural physical human–robot interaction in cooperative tasks where the human co-worker is allowed to modify both the spatial course of motion as well as the speed of execution at any stage, using a Frenet–Serret frame.
Abstract: In this paper we propose a novel approach for intuitive and natural physical human–robot interaction in cooperative tasks. Through initial learning by demonstration, robot behavior naturally evolves into a cooperative task, where the human co-worker is allowed to modify both the spatial course of motion as well as the speed of execution at any stage. The main feature of the proposed adaptation scheme is that the robot adjusts its stiffness in path operational space, defined with a Frenet–Serret frame. Furthermore, the required dynamic capabilities of the robot are obtained by decoupling the robot dynamics in operational space, which is attached to the desired trajectory. Speed-scaled dynamic motion primitives are applied for the underlying task representation. The combination allows a human co-worker in a cooperative task to be less precise in parts of the task that require high precision, as the precision aspect is learned and provided by the robot. The user can also freely change the speed and/or the trajectory by simply applying force to the robot. The proposed scheme was experimentally validated on three illustrative tasks. The first task demonstrates novel two-stage learning by demonstration, where the spatial part of the trajectory is demonstrated independently from the velocity part. The second task shows how parts of the trajectory can be rapidly and significantly changed in one execution. The final experiment shows two Kuka LWR-4 robots in a bi-manual setting cooperating with a human while carrying an object.
57 citations
Cites methods from "Passivity and Stability of Human–Ro..."
...It has been widely used in robotics as it preserves stable operationwith respect to the feedback and parallel interconnections of passive systems (Hatanaka 2015; Zhang and Cheah 2015)....
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References
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01 Jan 1991
TL;DR: Covers in a progressive fashion a number of analysis tools and design techniques directly applicable to nonlinear control problems in high performance systems (in aerospace, robotics and automotive areas).
Abstract: Covers in a progressive fashion a number of analysis tools and design techniques directly applicable to nonlinear control problems in high performance systems (in aerospace, robotics and automotive areas).
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TL;DR: The Complete Psychological Works of Sigmund Freud in English as mentioned in this paper is the first full paperback publication of the standard edition of the complete psychological works in English, containing twenty-four volumes.
Abstract: Indexes and Bibliographies. This collection of twenty-four volumes is the first full paperback publication of the standard edition of The Complete Psychological Works of Sigmund Freud in English
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TL;DR: It is shown that components of the manipulator impedance may be combined by superposition even when they are nonlinear, and a generalization of a Norton equivalent network is defined for a broad class of nonlinear manipulators which separates the control of motion from theControl of impedance while preserving the superposition properties of the Norton network.
Abstract: Manipulation fundamentally requires the manipulator to be mechanically coupled to the object being manipulated; the manipulator may not be treated as an isolated system. This three-part paper presents an approach to the control of dynamic interaction between a manipulator and its environment. In Part I this approach is developed by considering the mechanics of interaction between physical systems. Control of position or force alone is inadequate; control of dynamic behavior is also required. It is shown that as manipulation is a fundamentally nonlinear problem, the distinction between impedance and admittance is essential, and given the environment contains inertial objects, the manipulator must be an impedance. A generalization of a Norton equivalent network is defined for a broad class of nonlinear manipulators which separates the control of motion from the control of impedance while preserving the superposition properties of the Norton network. It is shown that components of the manipulator impedance may be combined by superposition even when they are nonlinear.
3,356 citations
06 Jun 1984
TL;DR: In this paper, a unified approach to kinematically constrained motion, dynamic interaction, target acquisition and obstacle avoidance is presented, which results in a unified control of manipulator behaviour.
Abstract: Manipulation fundamentally requires a manipulator to be mechanically coupled to the object being manipulated. A consideration of the physical constraints imposed by dynamic interaction shows that control of a vector quantity such as position or force is inadequate and that control of the manipulator impedance is also necessary. Techniques for control of manipulator behaviour are presented which result in a unified approach to kinematically constrained motion, dynamic interaction, target acquisition and obstacle avoidance.
3,292 citations
TL;DR: In this paper, an adaptive robot control algorithm is derived, which consists of a PD feedback part and a full dynamics feed for the compensation part, with the unknown manipulator and payload parameters being estimated online.
Abstract: A new adaptive robot control algorithm is derived, which consists of a PD feedback part and a full dynamics feedfor ward compensation part, with the unknown manipulator and payload parameters being estimated online. The algorithm is computationally simple, because of an effective exploitation of the structure of manipulator dynamics. In particular, it requires neither feedback of joint accelerations nor inversion of the estimated inertia matrix. The algorithm can also be applied directly in Cartesian space.
2,117 citations