Reaching for redundant arms with human-like motion and compliance properties
TL;DR: A novel controller for target reaching of redundant arms without trajectory planning, guaranteeing desired completion time and accuracy requirements without the need for trajectory planning and prior knowledge of robot dynamics is proposed.
About: This article is published in Robotics and Autonomous Systems.The article was published on 2014-12-01. It has received 21 citations till now. The article focuses on the topics: Control theory.
Citations
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TL;DR: A state feedback control scheme for variable stiffness actuated (VSA) robots, which guarantees prescribed performance of the tracking errors despite the low range of mechanical stiffness, is proposed.
Abstract: This paper is concerned with the design of a state feedback control scheme for variable stiffness actuated (VSA) robots, which guarantees prescribed performance of the tracking errors despite the low range of mechanical stiffness. The controller does not assume knowledge of the actual system dynamics nor does it utilize approximating structures (e.g., neural networks and fuzzy systems) to acquire such knowledge, leading to a low complexity design. Simulation studies, incorporating a model validated on data from an actual variable stiffness actuator (VSA) at a multi-degrees-of-freedom robot, are performed. Comparison with a gain scheduling solution reveals the superiority of the proposed scheme with respect to performance and robustness.
78 citations
TL;DR: Wang et al. as mentioned in this paper applied the swivel motion reconstruction approach to imitate human-like behavior using the kinematic mapping in robot redundancy, and proposed a novel incremental learning framework that combines an incremental learning approach with a deep convolutional neural network for fast and efficient learning.
Abstract: Recently, the human-like behavior on the anthropomorphic robot manipulator is increasingly accomplished by the kinematic model establishing the relationship of an anthropomorphic manipulator and human arm motions. Notably, the growth and broad availability of advanced data science techniques facilitate the imitation learning process in anthropomorphic robotics. However, the enormous dataset causes the labeling and prediction burden. In this article, the swivel motion reconstruction approach was applied to imitate human-like behavior using the kinematic mapping in robot redundancy. For the sake of efficient computing, a novel incremental learning framework that combines an incremental learning approach with a deep convolutional neural network is proposed for fast and efficient learning. The algorithm exploits a novel approach to detect changes from human motion data streaming and then evolve its hierarchical representation of features. The incremental learning process can fine-tune the deep network only when model drifts detection mechanisms are triggered. Finally, we experimentally demonstrated this neural network's learning procedure and translated the trained human-like model to manage the redundancy optimization control of an anthropomorphic robot manipulator (LWR4+, KUKA, Germany). This approach can hold the anthropomorphic kinematic structure-based redundant robots. The experimental results showed that our architecture could not only enhance the regression accuracy but also significantly reduce the processing time of learning human motion data.
51 citations
TL;DR: A prescribed performance signal for joint limit avoidance guarantees is proposed that can be utilized with both planned and on-line generated trajectories and can act as a null space velocity for the primary task velocity mapping.
49 citations
TL;DR: A novel selection scheme is proposed, which facilitates the choice of appropriate control approaches for given requirements, particularly for newcoming researchers to the field.
48 citations
TL;DR: A novel deep convolutional neural network (DCNN) structure for reconstruction enhancement and reducing online prediction time is proposed for managing redundancy control a 7 DoFs anthropomorphic robot arm (LWR4+, KUKA, Germany) for validation.
Abstract: Human-like behavior has emerged in the robotics area for improving the quality of Human-Robot Interaction (HRI). For the human-like behavior imitation, the kinematic mapping between a human arm and robot manipulator is one of the popular solutions. To fulfill this requirement, a reconstruction method called swivel motion was adopted to achieve human-like imitation. This approach aims at modeling the regression relationship between robot pose and swivel motion angle. Then it reaches the human-like swivel motion using its redundant degrees of the manipulator. This characteristic holds for most of the redundant anthropomorphic robots. Although artificial neural network (ANN) based approaches show moderate robustness, the predictive performance is limited. In this paper, we propose a novel deep convolutional neural network (DCNN) structure for reconstruction enhancement and reducing online prediction time. Finally, we utilized the trained DCNN model for managing redundancy control a 7 DoFs anthropomorphic robot arm (LWR4+, KUKA, Germany) for validation. A demonstration is presented to show the human-like behavior on the anthropomorphic manipulator. The proposed approach can also be applied to control other anthropomorphic robot manipulators in industry area or biomedical engineering.
47 citations
References
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TL;DR: A mathematical model is formulated which is shown to predict both the qualitative features and the quantitative details observed experimentally in planar, multijoint arm movements, and is successful only when formulated in terms of the motion of the hand in extracorporal space.
Abstract: This paper presents studies of the coordination of voluntary human arm movements. A mathematical model is formulated which is shown to predict both the qualitative features and the quantitative details observed experimentally in planar, multijoint arm movements. Coordination is modeled mathematically by defining an objective function, a measure of performance for any possible movement. The unique trajectory which yields the best performance is determined using dynamic optimization theory. In the work presented here, the objective function is the square of the magnitude of jerk (rate of change of acceleration) of the hand integrated over the entire movement. This is equivalent to assuming that a major goal of motor coordination is the production of the smoothest possible movement of the hand. Experimental observations of human subjects performing voluntary unconstrained movements in a horizontal plane are presented. They confirm the following predictions of the mathematical model: unconstrained point-to-point motions are approximately straight with bell-shaped tangential velocity profiles; curved motions (through an intermediate point or around an obstacle) have portions of low curvature joined by portions of high curvature; at points of high curvature, the tangential velocity is reduced; the durations of the low-curvature portions are approximately equal. The theoretical analysis is based solely on the kinematics of movement independent of the dynamics of the musculoskeletal system and is successful only when formulated in terms of the motion of the hand in extracorporal space. The implications with respect to movement organization are discussed.
4,226 citations
"Reaching for redundant arms with hu..." refers background in this paper
...Studies of human unconstrained reaching movements from one point to another reveal the following invariant kinematic characteristics: straight line paths, bell shaped velocities and joint configuration repeatability in repetitive motions [1–4]....
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TL;DR: Human subjects were instructed to point one hand to different visual targets which were randomly sequenced, using a paradigm which allowed two degrees of freedom, and trajectories of the hand in space were observed.
Abstract: Human subjects were instructed to point one hand to different visual targets which were randomly sequenced, using a paradigm which allowed two degrees of freedom (shoulder, elbow). The time course of the hand trajectory and the joint angular curves were observed. The latter exhibited patterns which change markedly for different movements, whereas the former preserve similar characteristics (in particular, a single peaked tangential velocity curve). The hypothesis is then formulated that the central command for these movements is formulated in terms of trajectories of the hand in space.
1,619 citations
"Reaching for redundant arms with hu..." refers background in this paper
...Studies of human unconstrained reaching movements from one point to another reveal the following invariant kinematic characteristics: straight line paths, bell shaped velocities and joint configuration repeatability in repetitive motions [1–4]....
[...]
TL;DR: It is shown that stabilization of the ldquounconstrainedrdquo system is sufficient to solve the stated problem and guarantees a uniform ultimate boundedness property for the transformed output error and the uniform boundedness for all other signals in the closed loop.
Abstract: A novel robust adaptive controller for multi-input multi-output (MIMO) feedback linearizable nonlinear systems possessing unknown nonlinearities, capable of guaranteeing a prescribed performance, is developed in this paper. By prescribed performance we mean that the tracking error should converge to an arbitrarily small residual set, with convergence rate no less than a prespecified value, exhibiting a maximum overshoot less than a sufficiently small prespecified constant. Visualizing the prescribed performance characteristics as tracking error constraints, the key idea is to transform the ldquoconstrainedrdquo system into an equivalent ldquounconstrainedrdquo one, via an appropriately defined output error transformation. It is shown that stabilization of the ldquounconstrainedrdquo system is sufficient to solve the stated problem. Besides guaranteeing a uniform ultimate boundedness property for the transformed output error and the uniform boundedness for all other signals in the closed loop, the proposed robust adaptive controller is smooth with easily selected parameter values and successfully bypasses the loss of controllability issue. Simulation results on a two-link robot, clarify and verify the approach.
1,475 citations
"Reaching for redundant arms with hu..." refers background or methods in this paper
...As shown in [24], prescribed performance of ei(t) in the sense of (5) or (6) for all t ≥ 0 is achieved by ensuring the boundedness of the transformed output error vector:...
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...It is based on the prescribed performance control methodology (PPC) introduced in [24]....
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Book•
01 Dec 1997
TL;DR: An introduction to kinematics Differential Kinematics and Statics Dynamics Trajectory Planning Motion Control Interaction Control Actuators and Sensors Control Architecture Appendices.
Abstract: Introduction Kinematics Differential Kinematics and Statics Dynamics Trajectory Planning Motion Control Interaction Control Actuators and Sensors Control Architecture Appendices A. Linear Algebra B. Rigid Body Mechanics C. Feedback Control
1,035 citations
"Reaching for redundant arms with hu..." refers background in this paper
...Let us define reaching as a regulation task for the task error e ∈ < given by the difference between the current task value in terms of the robot configuration q ∈ < and its desired constant value: e = D(q)− pd (2) As reaching targets may involve both position and orientation variables, for the orientation errors the outer product formulation, the Euler angle representation or quaternions may be used [33]....
[...]
TL;DR: The concept of task priority in relation to the inverse kinematic problem of redundant robot manipulators is introduced and the effectiveness of the proposed redundancy control scheme is shown.
Abstract: In this paper, we describe a new scheme for redundancy control of robot manipulators. We introduce the concept of task priority in relation to the inverse kinematic problem of redundant robot manipulators. A required task is divided into subtasks according to the order of priority. We propose to determine the joint motions of robot manipulators so that subtasks with lower priority can be performed utilizing re dundancy on subtasks with higher priority. This procedure is formulated using the pseudoinverses of Jacobian matrices. Most problems of redundancy utilization can be formulated in the framework of tasks with the order of priority. The results of numerical simulations and experiments show the effectiveness of the proposed redundancy control scheme.
933 citations
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