This paper presents motion strategy of a wall-climbing inspection robot SAFARI An algorithm of robot's legs movement is described. The movement sequence is chosen autonomously by the robot, respecting geometrical ...
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ISBN:
(纸本)8371434294
This paper presents motion strategy of a wall-climbing inspection robot SAFARI An algorithm of robot's legs movement is described. The movement sequence is chosen autonomously by the robot, respecting geometrical constraints of the robot's construction. robots behavior in an emergency situations when any of the legs cannot be sealed on a movement surface is also described. In one of the paragraphs direct and inverse kinematics for the SAFARI robot are presented. Then, in the following chapter another approach, named vector formulation of kinematics, is presented. Final section, before the summary, contains description of a software supervision of the robot's states, supporting an operator in monitoring of the robot's functioning.
This article presents a novel observer-based control system to achieve reactive motion generation for dynamic biped walking. The proposed approach combines a feedback controller with an online generated feet pattern t...
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This article presents a novel observer-based control system to achieve reactive motion generation for dynamic biped walking. The proposed approach combines a feedback controller with an online generated feet pattern to assure a stable gait. Using the desired speed of the robot, a preview control system derives the dynamics of the robot's body, and thereby the trajectory of its center of mass, to ensure a zero moment point (ZMP) movement, which results in a stable execution of the calculated step pattern. Extending the control system by an observer, based on this knowledge and the measured sensor values, compensates for errors in the model parameters and disturbances encountering while walking. (C) 2009 Elsevier B.V. All rights reserved.
This paper presents navigation and control of a robot for capturing a moving target using the vision system. A stereo camera is used to calculate the pose of the moving target (position and orientation). An Adaptive U...
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ISBN:
(纸本)9781538639269
This paper presents navigation and control of a robot for capturing a moving target using the vision system. A stereo camera is used to calculate the pose of the moving target (position and orientation). An Adaptive Unscented Kalman Filter (AUKF) is used to generate an optimal path to capture the moving object by estimating the state vector (position, orientation, linear and angular velocities) of the target. The Fuzzy Logic Adaptive System (FLAS) has been used to prevent the AUKF from divergence. The FLAS can evaluate the performance of UKF and tuning the factors in the weighted covariance to improve the accuracy of UKF. A new trajectory planning method for the space robot is proposed based on the information acquired from the vision system and estimation the linear and angular velocities of the target by AUKF. The results from simulation experiments were presented and discussed. It was concluded that the Fuzzy Adaptive Unscented Kalman Filter methods give more accurate results rather than the Unscented Kalman filter or Extended Kalman Filter.
In the present work, a new task space non-singular terminal sliding mode (TSM) manifold defined by non-linear integral equation of the first order with respect to the task tracking error and a kind of computed torque ...
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ISBN:
(纸本)9781728129754
In the present work, a new task space non-singular terminal sliding mode (TSM) manifold defined by non-linear integral equation of the first order with respect to the task tracking error and a kind of computed torque method are introduced to control four mecanum wheeled mobile robot (FMWMR). On account of the full rank of the Jacobian matrix of the omni-directional holonomic mechanism, the proposed control scheme is shown to be globally finitetime stable despite uncertain dynamic equations and (globally) unbounded disturbances acting on the FMWMR. Moreover, the proposed control law provides (locally) optimal solution. The numerical simulations carried out for a youBot platform with four mecanum wheels illustrate both the performance of the proposed control scheme and simultaneously its minimizing property for some practically useful objective function.
Aiming at the problem of balancing control of a cubical robot, this paper makes a research on the balancing control of a cubical robot balancing on its corner. Using the physical prototype of cubical robot we designed...
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ISBN:
(纸本)9781538619469
Aiming at the problem of balancing control of a cubical robot, this paper makes a research on the balancing control of a cubical robot balancing on its corner. Using the physical prototype of cubical robot we designed as the research object, the dynamic model is derived with Lagrangian method. A balancing controller is proposed base on a nonlinear control method-active disturbance rejection control (ADRC). There are three ADRC controllers in pitch, roll and yaw direction. The internal and external disturbance of the system are regarded as the total disturbances of the ADRC controller. The effectiveness of the controller is verified in the comparison with PID algorithm with the obtained expect effect. The controller developed can provide a base for further study for balancing control of a physical prototype cubical robot.
The paper presents a software implementation of the nonlinear model predictive control (NMPC) algorithm of Wen and Jung [8, 9] to a 6-degree-of-freedom robot manipulator. The implemented algorithm attempts to reduce t...
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ISBN:
(纸本)8371432720
The paper presents a software implementation of the nonlinear model predictive control (NMPC) algorithm of Wen and Jung [8, 9] to a 6-degree-of-freedom robot manipulator. The implemented algorithm attempts to reduce the error at the end of the prediction horizon rather than to find the optimal solution. This leads to reduction of computational burden. Simulations have been carried out for the mathematical model of the 6dof robot manipulator (Puma 560) and some exemplifying results are presented.
This paper deals with the decentralized predefined-time leaderless consensus formation control problem for nonholonomic multi-agent systems. First, the predefined-time average consensus problem is investigated. Distri...
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ISBN:
(纸本)9798350393972;9798350393965
This paper deals with the decentralized predefined-time leaderless consensus formation control problem for nonholonomic multi-agent systems. First, the predefined-time average consensus problem is investigated. Distributed observers, which interact with each other via an undirected communication topology, are designed to estimate, in a predefined-time, the average of their initial state using only local information. Then, based on these estimates, a predefined-time Vector-Field-Orientation (VFO) controller is applied, which guarantees that the multi-agent system achieves a desired formation. The VFO controller enables one to predict the paths for each agent and to avoid static obstacles. Some numerical results illustrate the interest of the proposed predefined-time leaderless consensus formation controller.
Accurate localisation of an indoor robot critically depends on the odometry calibration which varies with different types of floor surfaces. motioncontrol accuracy of robots can be improved by independently calibrati...
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ISBN:
(纸本)9781479984640
Accurate localisation of an indoor robot critically depends on the odometry calibration which varies with different types of floor surfaces. motioncontrol accuracy of robots can be improved by independently calibrating odometry parameters for each floor surface [1]. This paper presents a new robot floor classification system based on motor current measurements with compensation for variations in the floor inclination angles. The motor current is proportional to the rolling resistance on a flat floor when the robot travels at a constant velocity. We show that commonly occurring small deviations of less than one degree in the inclination of indoor floors significantly affects motor current measurements. The paper compensates for floor inclination variations with a low cost accelerometer. Floors are classified using a Support Vector Machine (SVM) with an accuracy of 95% for a 0.2 m travelling distance and 4 indoor surfaces that include similar carpets. Experimental results show that our proposed method significantly improves a previous floor classification system based on a colour sensor [1]. Our previous work has shown that correct floor classification can improve robotmotioncontrol through more accurate odometry calibration, localisation, mapping and path planning.
Human-robot Interaction (HRI) is pivotal in today's technological landscape, as robots become increasingly integrated into various aspects of human activity, spanning industrial, service, and healthcare sectors. E...
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ISBN:
(纸本)9798350393972;9798350393965
Human-robot Interaction (HRI) is pivotal in today's technological landscape, as robots become increasingly integrated into various aspects of human activity, spanning industrial, service, and healthcare sectors. Effective collaboration between humans and robots is essential for optimizing productivity, safety, and user experience. HRI also raises ethical and social considerations, highlighting the need for safe and ethical robot deployment and fostering trust among users. Graph neural networks (GNNs) offer a cutting-edge approach in HRI, enabling robots to model complex relational data and capture nuanced social interactions. By leveraging GNNs, robots can recognize human activities, infer intentions, and adapt their behavior accordingly, fostering natural and engaging interactions. In this paper, we utilize Graph Convolution Networks (GCNs) for datasets like AIR-Act2Act, which provide rich information for teaching social skills to robots and serve as benchmarks for action recognition tasks. By leveraging the spatial and temporal relationships encoded in 3D skeletal data, GNNs empower robots to perceive and interpret human behavior with sophistication, facilitating seamless interactions in real-world settings.
A general trajectory planner for optimal control problems is presented and applied to a robot system. The approach is based on timed elastic bands and nonlinear model predictive control. By exploiting the sparsity in ...
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ISBN:
(纸本)9781538619469
A general trajectory planner for optimal control problems is presented and applied to a robot system. The approach is based on timed elastic bands and nonlinear model predictive control. By exploiting the sparsity in the underlying optimization problems the computational effort can be significantly reduced, resulting in a real-time capable planner. In addition, a localization based switching strategy is employed to enforce convergence and stability. The planning procedure is illustrated in a robotics application using a realistic SCARA type robot.
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