Sambhunath Nandy

Time Delay Sliding Mode Control of Nonholonomic Wheeled Mobile Robot: Experimental Validation

In this endeavor, a hybrid control strategy has been proposed for composite path tracking control of a nonholonomic wheeled mobile robotic (WMR) system under parametric and nonparametric uncertainties. A WMR, often in practical circumstances, undergoes through various parametric changes. Moreover, modeling of WMR in presence of friction, slip or skid, backlash etc. is very difficult. These factors, which make the system model more cumbersome, are normally ignored but their effects are compensated through appropriate control methods. Conventional Sliding Mode Control (SMC) is such a method but it is susceptible to chattering due to high switching gains and reasonable tracking accuracy is sacrificed to avoid chattering. On the other hand, Time Delay Control (TDC) technique is highly efficient to assure robustness against unknown dynamics but it is unable to eliminate approximation errors that arise due to introduced delay. Considering the aforesaid difficulties of SM and TD controllers a hybrid control methodology christened as Time Delay Sliding Mode Control (SMC-TD) is adopted in this work for accurate path tracking of nonholonomic WMR. The SMC-TD is absolutely a judicious blending of SMC and TDC strategies aiming at elimination of the individual shortcomings while retaining the positive advantages. Detail features and advantages of the proposed controller are presented in greater length along with the experimental results, which are very promising.

Robust position control of an autonomous underwater vehicle: A comparative study

The highly non-linear and coupled dynamics of Autonomous Underwater Vehicles (AUVs), added with modeling errors, parametric uncertainties and payload variations pose a major challenge towards autonomous control of AUVs for various application requirements. Environmental hazards such as ocean currents sometimes dominate and make the control of underwater systems even more complicated. The proposed control technique addresses the design of a robust controller for reasonably accurate path tracking of AUVs incorporating the effects of above uncertain paradigms within some known bounds. It is well-known that measurement noise, which is associated with the navigational sensors, degrades the performance of the controller leading to substantial deviation from the reference path. Incorporation of sensor fusion technique, which is driven by sensors error characteristics, is necessary to improve the controller performance. Performance of the controller is verified using the real-life parameters an AUV, developed at CSIR-CMERI, Durgapur, India considering a few uncertainties.

Error modeling of Laser Range Finder for robotic application using time domain technique

Present day mobile robots are meant for very precise applications. For very precise applications of mobile robots, accurate estimation of inertial parameters depends upon the accuracy of mathematical model & as well as accuracy (error characteristics) of the individual sensor measurements. Sensor measurements are prone to various errors, which necessitates the detail modeling of sensors for estimation of useful signals from the noisy sensor measurements. Detail error modeling is essential to understand, identify & characterize the different types of noises present in the measured data using available mathematical techniques. This paper illustrates the frequency and time domain analysis techniques for characterization and identification of various noises present in the Laser Range Finder (Model: LMS200, SICK, Germany) measurements and their contribution to the overall noise statistics. A detailed methodology based on stochastic discrete time model is presented for Laser Range Finder error modeling.

Robust control of nonholonomic wheeled mobile robot with past information: Theory and experiment

In this article, a robust hybrid control method is presented for efficient path tracking control of a nonholonomic wheeled mobile robotic system under parametric and nonparametric variations. The present control law is a paradigm shift to control a wheeled mobile robot over a predefined trajectory by fusing the best features of the switching control logic as well as time-delayed control logic. The proposed hybrid control strategy aims at reducing the effort required for modeling the complex wheeled mobile robotic systems by approximating the unknown dynamics using input and feedback information of past time instances. Furthermore, the proposed methodology significantly reduces the approximation error arising from finite time-delay through the switching logic without any prior knowledge of the uncertainty bound. A new stability analysis for the time-delayed control is proposed which establishes an analytical relation between the controller performance and the approximation error. Performance of the proposed hybrid controller is tested with a real-life wheeled mobile robot and improved tracking performance is observed compared to conventional robust control strategies even with the incorporation of dynamic parametric uncertainties.

A modular approach to detailed dynamic formulation and control of wheeled mobile robot

Presently, nonholonomic mobile robots driven by wheels are being used for variety of applications where high velocity maneuvering control is very essential. The need for accurate formulation of system dynamics incorporating each & every moving parts of the robot is very important for faster movement & precise applications. This paper represents the detailed dynamic formulation based on overall robots kinetic energy along with an advanced control scheme. Actuator dynamics have been also considered to achieve precise motion control and to design a simple controller with a low cost sensor suite. A modular approach has been adopted to derive the kinetic energy of the robot accurately & thereafter to evaluate required equations of motion. A feedback linearization based path following controller with online gain scheduling has been designed to control the mobile robot through various paths. The methodology adopted for path following control deals explicitly with detail robot-actuator dynamics and it overcomes stringent initial condition constraints. The simulation has been carried out with the parameters of a real robot and the simulation results illustrate very promising performance due to incorporation of detail robot-actuator dynamics.

Estimation of Mechanical Impedance of a Flexible Transmission using Partial Knowledge of Elastic Characteristic and its Validation

Use of flexible joints in robotic system is the recent trend in applications involving physical human robot interaction. A compliant transmission introduces the flexibility for intrinsically safe robots, whereas the ability to vary Impedance recovers some of the lost performance due to presence of compliance. Stiffness/impedance variability needs presence of nonlinearity in the passive elastic and/or damping characteristic. In controlling robot joint impedance knowledge of stiffness/impedance of transmission becomes necessary. Obtaining a predetermined model of the transmission always introduces inaccuracies and uncertainties with varying characteristics of the transmission with time and ambiance. It proves almost indispensable to estimate the joint stiffness/ impedance during operation for reliable control of variable impedance. It also proves to be a difficult task to estimate impedance/stiffness online on the basis of sensory information of differential motion and differential force. In this article, in order to estimate stiffness of the transmission, a favourable characteristic of the transmission has been exploited. The flexible transmission is designed with a first principle obtained from property of biological muscle so that it maintains an affine relationship between the stiffness and the force being transmitted. This article implements an Extended Kalman Filter algorithm for on-the-fly estimation of stiffness (along with impedance) exploiting the linearity property for applicability of EKF and to reduce complexity of the procedure. The effectiveness of the proposed estimator is examined through experiments on the mechanical transmission designed from the above biological principle. The results are further validated by comparing with the results of estimation using full parameter identification of specified model of the transmission.

Application of Particle Filtering Technique for sensor fusion in mobile robotics

Accurate position estimation is very essential for successful operation of any autonomous mobile robots. Generally, Extended Kalman Filter (EKF) is used to fuse multiple low cost sensor information for better position estimation of mobile robots. However, due to the first-order approximation while performing linearization of the nonlinear model in the EKF, it will introduce large estimation errors over the time. In order to reduce the significant estimation errors, the Particle Filter (PF) is presently used as a modern sensor fusion methodology applied to mobile robotics due to its generic nature to tackle uncertainty & nonlinearity. This paper illustrates application of Particle Filtering Technique for reliable estimation of the state vector of a mobile robot in association with proprioceptive (Odometry) and exteroceptive (Laser Range Finder) sensors for efficient control. The paper also presents a comparison of the performance of the EKF & PF techniques for the estimation of the states & control of the mobile robot and establishes the superiority of PF over EKF.

Keypoints based laser scan matching — A robust approach

This paper aims at development of a robust keypoints based scan matching (KSM) methodology for 2D laser data applied to mobile robot navigation. In this method feature points are first transformed to grid points, and then represented in the form of image. Keypoints are extracted using Harris corner detection method and finally matching is done by RANSAC method. Real world experiments have been carried out to evaluate the utility and robustness of the proposed method. A comparison has been drawn with scan matching technique with ICP method. The proposed method might be used in a robust manner for mobile robot navigation with moderate computational complexity.