Journal ArticleDOI
Reaching for redundant arms with human-like motion and compliance properties
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TLDR
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.read more
Citations
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Journal ArticleDOI
Prescribed Performance Tracking of a Variable Stiffness Actuated Robot
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.
Journal ArticleDOI
An Incremental Learning Framework for Human-Like Redundancy Optimization of Anthropomorphic Manipulators
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.
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Kinematic control of redundant robots with guaranteed joint limit avoidance
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.
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An introductory review of active compliant control
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.
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Deep Neural Network Approach in Human-Like Redundancy Optimization for Anthropomorphic Manipulators
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.
References
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Journal ArticleDOI
Robust Partial-State Feedback Prescribed Performance Control of Cascade Systems With Unknown Nonlinearities
TL;DR: The proposed control scheme is of low complexity, utilizes partial state feedback and requires reduced levels of a priori system knowledge, and can be easily extended to systems affected by bounded state measurement errors, as well as to MIMO nonlinear systems in block triangular form.
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Prescribed performance tracking for flexible joint robots with unknown dynamics and variable elasticity
TL;DR: The developed full state feedback controller, is realized without incorporating knowledge relative to the actual system nonlinearities, and no approximators are employed to acquire such information.
Journal ArticleDOI
Human-Intent Detection and Physically Interactive Control of a Robot Without Force Sensors
TL;DR: A switching scheme is developed that goes between the modes of pure impedance control with a fixed-position reference and interactive control under human intent and puts the robot into interactive mode, if there is any.
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Neuro-Adaptive Force/Position Control With Prescribed Performance and Guaranteed Contact Maintenance
TL;DR: The unknown nonlinearities that arise owing to the uncertainties in the force deformation model are approximated by a neural network linear in the weights and it is proven that the neural network approximation holds for all time irrespective of the magnitude of the modeling error, the disturbances, and the controller gains.
Journal ArticleDOI
Model-free robot joint position regulation and tracking with prescribed performance guarantees
TL;DR: The problem of robot joint position control with prescribed performance guarantees is considered; the control objective is the error evolution within prescribed performance bounds in both problems of regulation and tracking.
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