Jayantha Katupitiya

Estimating first-order geometric parameters and monitoring contact transitions during force controlled compliant motion

This paper uses (linearized) Kalman filters to estimate first-order geometric parameters (i.e., orientation of contact normals and location of contact points) that occur in force-controlled compliant motions. The time variance of these parameters is also estimated. In addition, transitions between contact situations can be monitored. The contact between the manipulated object and its environment is general, i.e., multiple contacts can occur at the same time, and both the topology and the geometry of each single contact are arbitrary. The two major theoretical contributions are 1) the integration of the general contact model, developed previously by the authors, into a state-space form suitable for recursive processing; and 2) the use of the reciprocity constraint between ideal contact forces and motion freedoms as the “measurement equation” of the Kalman filter. The theory is illustrated by full 3-D experiments. The approach of this paper allows a breakthrough in the state of the art dominated by the classical, orthogonal contact models of Mason that can only cope with a limited (albeit important) subset of all possible contact situations.

On-tree fruit recognition using texture properties and color data

As a prelude to using stereo vision to accurately locate apples in an orchard, this paper presents a vision based algorithm to locate apples in a single image. On-tree situations of contrasting red and green apples as well as green apples in the orchard with poor contrast have been considered. The study found out that the redness in both cases of red and green apples can be used to differentiate apples from the rest of the orchard. Texture based edge detection has been combined with redness measures, and area thresholding followed by circle fitting, to determine the location of apples in the image plane. In the case of severely cluttered environments, Laplacian filters have been used to further clutter the foliage arrays by edge enhancement so that texture differences between the foliage and the apples increased thereby facilitating the separation of apples from the foliage. Results are presented that show the recognition of red and green apples in a number of situations as well as apples that are clustered together and/or occluded.

Human robot interaction: application to smart wheelchairs

Addresses the problem of human robot interaction with application to the design of assistive devices. We describe the design and development of a prototype of a smart wheelchair that can be commanded by a rider. Specifically, we focus on (a) the vision-based human interaction interface; (b) the suite of sensors on the chair, and (c) the software architecture and the control algorithms used to control the chair.

Global Correlation Based Ground Plane Estimation Using V-Disparity Image

This paper presents the estimation of the position of the ground plane for navigation of on-road or off-road vehicles, in particular for obstacle detection using stereo vision. Ground plane estimation plays an important role in stereo vision based obstacle detection tasks. V-disparity image is widely used for ground plane estimation. However, it heavily relies on distinct road features which may not exist. In here, we introduce a global correlation method to extract the position of the ground plane in V-disparity image even without distinct road features.

Nonlinear sliding mode control of an unmanned agricultural tractor in the presence of sliding and control saturation

The paper considers the problem of automatic path tracking by autonomous farming vehicles subject to wheel slips, which are characteristic for agricultural applications. Two guidance laws are proposed to solve this problem, and both explicitly take into account the constraints on the steering angle and ensure tracking an arbitrarily curved path. The first law is implemented by the pure sliding-mode controller, whereas the second one combines the sliding mode approach with a smooth nonlinear control law and requests control chattering at the reduced amplitude as compared with the first law. Mathematically rigorous proofs of global convergence and robust stability of the proposed guidance laws are presented. In doing so, the slipping effects are treated as bounded uncertainties. Simulation results and real world experiments confirm the applicability and performance of the proposed guidance approach.

Covariance profiling for an adaptive Kalman filter to suppress sensor quantization effects

This paper presents a generic approach to model the noise covariance associated with discrete sensors such as incremental encoders and low resolution analog to digital converters. The covariance is then used in an adaptive Kalman filter that selectively and appropriately carries out measurement updates. The temporal as well as system state measurements are used to predict the quantization error of the measurement signal. The effectiveness of the method is demonstrated by applying the technique to incremental encoders of varying resolutions. Simulation of an example system with varying encoder resolutions is presented to show the performance of the new filter. Results show that the new adaptive filter produces more accurate results while requiring a lower resolution encoder than a similarly designed conventional Kalman filter, especially at low velocities.

An active axis control system for a conventional CNC machine

A non-invasive approach to implement an active axis controller for a conventional CNC machine is presented. To develop the system a two-stage approach has been taken. In stage one, a generic external axis controller is designed to bring the machine under the real-time control of an external computer. The external controller is interfaced to the CNC machine via the Manual Pulse Generator (MPC) inputs. The external controller uses a special interface to read the machine position. Stage two is the design of the active axis controller. To achieve this, a sensor feedback loop is added to the external controller to enable visual servoing. The developed active axis controller is used to actively track a profile using Visual feedback. The results presented compares the speed of response of the external axis controller with that of the speed of response of the original CNC controller in linear interpolation motion. The accuracy in the performance of the active axis controller is demonstrated by presenting the results of active visual tracking.

Simulation of a tractor-implement model under the influence of lateral disturbances

This work presents the derivation of a comprehensive mathematical model for an off-road vehicle such as an agricultural tractor that drags behind it a heavy implement. The models are being developed with the aim of designing robust controllers that will enable the high precision control of the implements trajectory. The developed model is subjected to real conditions, such as ground undulation and uncertainty, sloping terrain, tyre slippage, and constrained steering of the tractor. The implement is assumed to possess independently steered wheels for aiding in implement alignment. A complete model is presented and simulated under varying conditions. Primarily this work demonstrates and validates the trailed vehicle system behavior when the trailing implement is subjected to large drag forces due to ground engagement and the significantly large lateral disturbances that occur in real life broad acre farming conditions.

Detection of non-flat ground surfaces using V-Disparity images

Ground plane detection plays an important role in stereo vision based obstacle detection methods. Recently, V-Disparity image has been widely used for ground plane detection. The existing approach based on V-Disparity image can detect flat ground successfully but have difficulty in detecting non-flat ground. In this paper, we discuss the representation of non-flat ground in V-Disparity image, based on which we propose a method to detect non-flat ground using V-Disparity image.

Agricultural robotics: A streamlined approach to realization of Autonomous Farming

This paper presents a streamlined approach to future Precision Autonomous Farming (PAF). It focuses on the preferred specification of the farming systems including the farming system layout, sensing systems and actuation units such as tractor-implement combinations. The authors propose the development of the Precision Farming Data Set (PFDS) which is formed off-line before the commencement of the crop cultivation and discusses its use in accomplishing reliable, cost effective and efficient farming systems. The work currently in progress towards the development of autonomous farming vehicles and the results obtained through detailed mathematical analysis of example actuation units will also be presented.