Ottar L. Osen

Side-to-side 3D coverage path planning approach for agricultural robots to minimize skip/overlap areas between swaths

Automated path planning is an important tool for the automation and optimization of field operations. It can provide the waypoints required for guidance, navigation and control of agricultural robots and autonomous tractors throughout the execution of these field operations. Typical field operations?are repetitively required nearly every cropping season and therefore it should be carried out in a manner that maximizes the yield and minimizes operational cost, time and environmental impact taking into account the topographic land features. Current 3D terrain field coverage path planning algorithms are simply 2D coverage path planning projected into 3D through field terrain represented by the fields Digital Elevation Model (DEM). When projecting 2D coverage plan into its 3D counterpart, the actual distance between adjacent paths on the topographic surface either increases or decreases, and consequently there might be skips or overlaps between adjacent paths on the slopes. In addition, when the machine rolls on slopes the effective width of the implement decreases by a similar amount to double this error and complicates the problem. Skips and overlaps can lead to an inefficient use of land and resources. In this paper, a numerical approach to estimate the total skip/overlap areas is developed and applied to determine the optimum-driving angle that minimizes this impact. Also, a novel side-to-side 3D coverage path planning approach, which ensures zero skips/overlaps regardless of the topographical nature of the field terrain, is developed. The approaches developed in this paper are tested and validated using a hypothetical test field of a tailored terrain and a real experimental field of uneven terrain nature. The proposed approaches illustrated that a significant percentage of uncovered area could be saved if appropriate driving angle is chosen and if a side-to-side 3D coverage is used. We developed a more efficient 3D field coverage approach compared to existing approaches.We developed a numerical approach to examine the efficiency of 3D coverage algorithms in terms of skip/overlap areas.We developed side-to-side 3D field coverage approach, which ensure 100% coverage regardless of the topographical nature of the field surface.Simulation and real field experiments are conducted to prove the efficiency and superiority of the developed approaches.

Intelligent computer-automated crane design using an online crane prototyping tool

In an accompanying paper submitted concurrently to this conference, we present our first complete version of a generic and modular software framework for intelligent computer-automated product design. The framework has been implemented with a client-server software architecture that automates the design of offshore cranes. The framework was demonstrated by means of a case study where we used a genetic algorithm (GA) to optimise the crane design of a real and delivered knuckleboom crane. For the chosen objective function, the optimised crane design outperformed the real crane. In this paper, we augment our aforementioned case study by implementing a new crane optimisation client in Matlab that uses a GA both for optimising a set of objective functions and for multi-objective optimisation. Communicating with an online crane prototyping tool, the optimisation client and its GA are able to optimise crane designs with respect to two selected design criteria: the maximum safe working load and the total crane weight. Our work demonstrates the modularity of the software framework as well as the viability of our approach for intelligent computer-automated design, whilst the results are valuable for informing future directions of our research.

A Computer-Automated Design Tool For Intelligent Virtual Prototyping Of Offshore Cranes.

In close collaboration with the maritime industry, virtual prototyping with maritime application has been an important research topic for Aalesund University College for some years. In this paper, we describe the development of a computer-automated design tool for intelligent virtual prototyping of offshore cranes. Our work is part of a research project funded by the Research Council of Norway and takes place in close cooperation with two partners from the maritime industry. A literature review of virtual prototyping, computer-automated design, and modelling and simulation of offshore cranes sets the stage for the description of a design tool whose main components consist of a computational model, a simulator, and a genetic algorithm. We show how domain-specific constraints can be accounted for in conjunction with an automated optimisation procedure of design parameters to yield crane specifications that closely match the desired design criteria. Limitations of slewing rings and hydraulic cylinders are of particular importance in offshore crane design and are used as an example of the multitude of design calculations that form the computational model. Being work in progress, we report on completed parts and the work that remains.

A Software Framework For Intelligent Computer-Automated Product Design

For many years, NTNU in Ålesund (formerly Aalesund University College) has maintained a close relationship with the maritime industrial cluster, centred in the surrounding geographical region, thus acting as a hub for both education, research, and innovation. Of many common relevant research topics, virtual prototyping is currently one of the most important. In this paper, we describe our first complete version of a generic and modular software framework for intelligent computer-automated product design. We present our framework in the context of design of offshore cranes, with easy extensions to other products, be it maritime or not. Funded by the Research Council of Norway and its Programme for Regional R&D and Innovation (VRI), the work we present has been part of two separate but related research projects (grant nos. 241238 and 249171) in close cooperation with two local maritime industrial partners. We have implemented several software modules that together constitute the framework, of which the most important are a server-side crane prototyping tool (CPT), a client-side web graphical user interface (GUI), and a client-side artificial intelligence for product optimisation (AIPO) module that uses a genetic algorithm (GA) library for optimising design parameters to achieve a crane design with desired performance. Communication between clients and server is achieved by means of the HTTP and WebSocket protocols and JSON as the data format. To demonstrate the feasibility of the fully functioning complete system, we present a case study where our computer-automated design was able to improve the existing design of a real and delivered 50-tonnes, 2.9 million EUR knuckleboom crane with respect to some chosen desired design criteria. Our framework being generic and modular, both clientside and server-side modules can easily be extended or Corresponding author: Robin T. Bye, robin.t.bye@ntnu.no. replaced. We demonstrate the feasibility of this concept in an accompanying paper submitted concurrently, in which we create a simple product optimisation client in Matlab that uses readily available toolboxes to connect to the CPT and optimise various crane designs by means of a GA. In addition, our research team is currently developing a winch prototyping tool to which our existing AIPO module can connect and optimise winch designs with only small configuration changes. This work will be published in the near future.

An Interval Type-2 Fuzzy Logic System for Assessment of Studentsź Answer Scripts under High Levels of Uncertainty

The proper system for evaluating the learning achievement of students is the key to realizing the purpose of education and learning. Traditional grading methods are largely based on human judgments, which tend to be subjective. In addition, it is based on sharp criteria instead of fuzzy criteria and suffers from erroneous scores assigned by indifferent or inexperienced examiners, which represent a rich source of uncertainties, which might impair the credibility of the system. In an attempt to reduce uncertainties and provide more objective, reliable, and precise grading, a sophisticated assessment approach based on type-2 fuzzy set theory is developed. In this paper, interval type-2 (IT2) fuzzy sets, which are a special case of the general T2 fuzzy sets, are used. The transparency and capabilities of type-2 fuzzy sets in handling uncertainties is expected to provide an evaluation system able to justify and raise the quality and consistency of assessment judgments.

Analysis and modeling of sensor data for ship motion prediction

This paper presents an analyzing and modeling scheme that can dig into the ship sensor data to generate models for ship motion prediction. As the raw sensor data contains information that is noisy and discontinuous, three data cleaning methods used for noise reduction, data continuing and resampling are developed. According to specific ship applications, various ship motion constraints are designed to filter and establish meaningful data sets which will be used in the modeling step. Correlation analysis within the data sets is performed to figure out how significant the sensor data contributes to the predictive target. An flexible neural network based modeling mechanism is implemented, in which the user can design the model based on the correlation analysis. By training and testing the neural network using the generated data sets, the ship motion predictive model is obtained. Through a case study of fine maneuvering, the scheme is verified efficient in analyzing and modeling sensor data for ship motion prediction.

Grey wolf optimizer (GWO) for automated offshore crane design

In this paper, a new meta-heuristic optimization algorithm called Grey Wolf Optimizer (GWO) is applied to offshore crane design. An offshore crane is a pedestal-mounted elevating and rotating lifting device used to transfer materials or personnel to or from marine vessels, barges and structures whereby the load can be moved horizontally in one or more directions and vertically. Designing and building offshore cranes is a very complex process. It depends on the configuration of a large set of design parameters and is characterized by increased workability and functionality for the owner and cost effectiveness in the total cost of ownership. In an attempt to reduce time and cost involved in the design process, this paper defines a best set of design parameters and uses GWO for the automatic configuration of this set of parameters in a manner that increases the maximum safe working load of the crane and reduces its total weight. Results are verified by a comparative study with other Evolutionary Algorithms (EAs). Results show that the GWO algorithm is able to provide very competitive results compared to these well-known meta-heuristics.

A bio-inspired swimming robot for marine aquaculture applications: From concept-design to simulation

This paper presents the development of a bio-inspired swimming robot from concept design to simulation for marine aquaculture applications. Based on investigation of several fish motions, the Manta ray is found to be the most suitable mock object since the flapping pectoral fin features long-endurance, low noise, high payload capacity, good stability and maneuverability. Through a comprehensive analysis of the structure of Manta ray, the shape proportional relationship between the body and the pectoral fins is obtained. Even though the concept design simplifies the structure, major functional components are retained. By applying two degrees of freedoms to each segment of the pectoral fin, the propulsion mechanism allow the robotic fish to swim in 3D. In addition, a thrust analysis is performed for a good understanding of the fishs aquatic locomotion principle. The flapping motion is decomposed into two orthogonal waves and realized on the robotic fish, taking advantages of sine generators. Simulation experiments including motion comparison, speed and turning tests verify the correctness of the robotic fishs structure and its propulsion mechanisms.

A Comparison Between Optimization Algorithms Applied to Offshore Crane Design Using an Online Crane Prototyping Tool

Offshore crane design requires the configuration of a large set of design parameters in a manner that meets customers’ demands and operational requirements, which makes it a very tedious, time-consuming and expensive process if it is done manually. The need to reduce the time and cost involved in the design process encourages companies to adopt virtual prototyping in the design and manufacturing process. In this paper, we introduce a server-side crane prototyping tool able to calculate a number of key performance indicators of a specified crane design based on a set of about 120 design parameters. We also present an artificial intelligence client for product optimisation that adopts various optimization algorithms such as the genetic algorithm, particle swarm optimization, and simulated annealing for optimising various design parameters in a manner that achieves the crane’s desired design criteria (e.g., performance and cost specifications). The goal of this paper is to compare the performance of the aforementioned algorithms for offshore crane design in terms of convergence time, accuracy, and their suitability to the problem domain.

A Game-Based Learning Framework For Controlling Brain-Actuated Wheelchairs.

Paraplegia is a disability caused by impairment in motor or sensory functions of the lower limbs. Most paraplegic subjects use mechanical wheelchairs for their movement, however, patients with reduced upper limb functionality may benefit from the use of motorised, electric wheelchairs. Depending on the patient, learning how to control these wheelchairs can be hard (if at all possible), timeconsuming, demotivating, and to some extent dangerous. This paper proposes a game-based learning framework for training these patients in a safe, virtual environment. Specifically, the framework utilises the Emotiv EPOC EEG headset to enable brain wave control of a virtual electric wheelchair in a realistic virtual world game environment created with the Unity 3D game engine.