Position-Based Visual Servoing of a Mobile Robot with an Automatic Extrinsic Calibration Scheme

Robotica ◽  
2019 ◽  
Vol 38 (5) ◽  
pp. 831-844 ◽  
Author(s):  
Radhe Shyam Sharma ◽  
Santosh Shukla ◽  
Laxmidhar Behera ◽  
Venkatesh K. Subramanian
Keyword(s):  
Mobile Robot ◽  
Gradient Descent ◽  
Visual Servoing ◽  
Sliding Mode ◽  
Single Experiment ◽  
Novel Approach ◽  
Position And Orientation ◽  
Estimation And Control ◽  
Adaptive Nature ◽  
And Control

SUMMARYIn this paper, we present and implement a novel approach for position-based visual servoing. The challenge of controlling the mobile robot while simultaneously estimating the camera to mobile robot transformation is solved. This is achieved using gradient descent (GD)-based estimation and the sliding-mode approach. The GD approach allows online parameter estimation for controlling the robot to achieve a desired position and orientation. The adaptive nature of the parameters demonstrates the robustness of the system. In contrast to existing work, the proposed technique achieves both estimation and control tasks in a single experiment. Simulation and experimental results are provided to validate the performance of the proposed scheme.

Center of gravity estimation and control for a field mobile robot with a heavy manipulator

2009 ◽  
Author(s):  
Jesus Morales ◽  
Jorge L. Martinez ◽  
Anthony Mandow ◽  
Javier Seron ◽  
Alfonso Garcia-Cerezo ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Center Of Gravity ◽  
Estimation And Control ◽  
And Control ◽  
Gravity Estimation

Robust Sensors-Fault-Tolerance With Sliding Mode Estimation and Control for PMSM Drives

2018 ◽  
Vol 23 (1) ◽  
pp. 17-28 ◽  
Author(s):  
Suneel Kumar Kommuri ◽  
Sang Bin Lee ◽  
Kalyana Chakravarthy Veluvolu
Keyword(s):  
Fault Tolerance ◽  
Sliding Mode ◽  
Mode Estimation ◽  
Estimation And Control ◽  
And Control

Estimation and control of the attitude of a dynamic mobile robot using internal sensors

1992 ◽  
Vol 7 (2) ◽  
pp. 159-178 ◽  
Author(s):  
Osamu Matsumoto ◽  
Shuuji Kajita ◽  
Kazuo Tani
Keyword(s):  
Mobile Robot ◽  
Estimation And Control ◽  
And Control

The Problems of Competence Approach

2016 ◽  
pp. 31-43
Author(s):  
Vladimir Zelichenko ◽  
Irina Bushueva
Keyword(s):  
Detailed Analysis ◽  
Sliding Mode ◽  
Learning Systems ◽  
Main Attention ◽  
Mathematical Formula ◽  
Educational Standard ◽  
E Learning ◽  
Estimation And Control ◽  
And Control

In this chapter the authors consider the problems of competence approach, the estimation and the control in world E-Learning Systems. The main attention is on the problem of the formation of evaluation competencies. We consider detailed examples showing how, at a certain stage, learning can be assessed in varying levels of competence. Based on a detailed analysis of the educational standard and assessment of proposed methodology, the authors formalize this assessment and express it by a mathematical formula. The problems of estimation and control are proposed to be solved using feedback based on sliding mode by Prof. Vardan Mkrttchian.

scholarly journals Trajectory tracking control of an amphibian robot with operational capability

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986542 ◽  
Author(s):  
Fujie Yu ◽  
Yuan Chen
Keyword(s):  
Sliding Mode ◽  
Tracking Error ◽  
Control Force ◽  
Power Switching ◽  
Trajectory Tracking Control ◽  
Operational Capability ◽  
Kinematic Models ◽  
Position And Orientation ◽  
And Control ◽  
Amphibious Robot

Although the traditional amphibious robot has the ability of multi-space motion, it has the disadvantage of low power utilization and no operational capability. In order to make it competent in an extremely complex environment, we studied the structural design and control of amphibian robot with operational capability. First, in order to make the robot have the ability of flying in the sky, moving on land, and swimming in the water, a “bevel variant” mechanism for power switching is designed. Then, taking the uncertainty of the kinetic parameters and external influences into account, the kinetic and kinematic models of the system are established. Next, a sliding mode controller that outputs control force for the system and a quadratic calculation optimization algorithm for inverse kinematics solution are designed. Finally, the simulation platform for the system is built based on MATLAB. The simulation results show that when the system is in the land and air flight stages, the vehicle position and orientation tracking error are within ±0.05 m and ±2°, respectively. When the system is in the underwater stage, the end effector position and orientation tracking error are within ±0.15 m and ±3.0°, respectively.

scholarly journals Development of Online Adaptive Traction Control for Electric Robotic Tractors

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3394
Author(s):  
Idris Idris Sunusi ◽  
Jun Zhou ◽  
Chenyang Sun ◽  
Zhenzhen Wang ◽  
Jianlei Zhao ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Sliding Mode ◽  
Interpolation Method ◽  
Field Tests ◽  
Soil Disturbance ◽  
Wheel Slip ◽  
Slip Ratio ◽  
Optimal Values ◽  
Estimation And Control ◽  
And Control

Estimation and control of wheel slip is a critical consideration in preventing loss of traction, minimizing power consumptions, and reducing soil disturbance. An approach to wheel slip estimation and control, which is robust to sensor noises and modeling imperfection, has been investigated in this study. The proposed method uses a simplified form of wheels longitudinal dynamic and the measurement of wheel and vehicle speeds to estimate and control the optimum slip. The longitudinal wheel forces were estimated using a robust sliding mode observer. A straightforward and simple interpolation method, which involves the use of Burckhardt tire model, instantaneous values of wheel slip, and the estimate of longitudinal force, was used to determine the optimum slip ratio that guarantees maximum friction coefficient between the wheel and the road surface. An integral sliding mode control strategy was also developed to force the wheel slip to track the desired optimum value. The algorithm was tested in Matlab/Simulink environment and later implemented on an autonomous electric vehicle test platform developed by the Nanjing agricultural university. Results from simulation and field tests on surfaces with different friction coefficients (μ) have proved that the algorithm can detect an abrupt change in terrain friction coefficient; it can also estimate and track the optimum slip. More so, the result has shown that the algorithm is robust to bounded variations on the weight on the wheels and rolling resistance. During simulation and field test, the system reduced the slip from non-optimal values of about 0.8 to optimal values of less than 0.2. The algorithm achieved a reduction in slip ratio by reducing the torque delivery to the wheel, which invariably leads to a reduction in wheel velocity.

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