S. Veera Ragavan

Towards an Ontology for Autonomous Robots

The IEEE RAS Ontologies for Robotics and Automation Working Group is dedicated to developing a methodology for knowledge representation and reasoning in robotics and automation. As part of this working group, the Autonomous Robots sub-group is tasked with developing ontology modules for autonomous robots. This paper describes the work in progress on the development of ontologies for autonomous systems. For autonomous systems, the focus is on the cooperation, coordination, and communication of multiple unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and autonomous underwater vehicles (AUVs). The ontologies serve as a framework for working out concepts of employment with multiple vehicles for a variety of operational scenarios with emphasis on collaborative and cooperative missions.

Way point based deliberative path planner for navigation

We present and implement a Genetic Algorithm (GA) based deliberative path planning algorithm using waypoints for navigation of Robots and AGVs. The Waypoint Navigation System is advantageous as it does not require a complete knowledge of the environment and can replace traditional robot navigation systems. The proposed GA for Robot navigation problem is NP-hard and Multi-objective. The performance of the implemented GA is compared with the results obtained from two popular algorithms namely the Dijikstras algorithm and A* algorithms. We propose a new Representation that reduces the size of the chromosome array for large number of waypoints; the proposed GA has faster convergence and obtains near optimal solutions. The system has been developed for a near real-time experiment using a Matlab engine located on an online server. An integrated system complete with the required Hardware was constructed for the purpose of testing the performance of the various algorithms using a real world Geographical Information System (GIS) and actual node data (waypoints) of Kuala Lumpur City. The proposed new system has been tested and is found to be suitable for adaptation in robot navigation, path planning and intelligent traffic guidance systems.

Requirements for building an ontology for autonomous robots

IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous robotics. This paper aims to present the work in-progress developed by the autonomous robotics (AuR) subgroup. This group aims to extend the core ontology for robotics and automation to represent more specific concepts and axioms that are commonly used in autonomous robots.,For autonomous robots, various concepts for aerial robots, underwater robots and ground robots are described. Components of an autonomous system are defined, such as robotic platforms, actuators, sensors, control, state estimation, path planning, perception and decision-making.,AuR has identified the core concepts and domains needed to create an ontology for autonomous robots.,AuR targets to create a standard ontology to represent the knowledge and reasoning needed to create autonomous systems that comprise robots that can operate in the air, ground and underwater environments. The concepts in the developed ontology will endow a robot with autonomy, that is, endow robots with the ability to perform desired tasks in unstructured environments without continuous explicit human guidance.,Creating a standard for knowledge representation and reasoning in autonomous robotics will have a significant impact on all R&A domains, such as on the knowledge transmission among agents, including autonomous robots and humans. This tends to facilitate the communication among them and also provide reasoning capabilities involving the knowledge of all elements using the ontology. This will result in improved autonomy of autonomous systems. The autonomy will have considerable impact on how robots interact with humans. As a result, the use of robots will further benefit our society. Many tedious tasks that currently can only be performed by humans will be performed by robots, which will further improve the quality of life. To the best of the authors’knowledge, AuR is the first group that adopts a systematic approach to develop ontologies consisting of specific concepts and axioms that are commonly used in autonomous robots.

Design of a Mechatronic Drive Train with Regenerative Braking

Building a research framework for a Parallel Hydraulic Hybrid (PHH) Prototype with Hydraulic Regenerative Braking and Launch Assist (HRB/HLA) System for small and medium sized vehicles has been attempted. The objective of this work is to capture lost Kinetic Energy during braking and store that captured energy in a pressurized accumulator to be used again to assist accleration. The experimental implementation and validation of the Regenerative Braking System concept for light vehicles has been done using a go-kart powered by a single cylinder Honda engine to demonstrate energy savings in a real life braking scenario. A light weight test system accommodating all the Hydraulic Breaking System components mounted at the rear of the go-kart has been successfully built and tested.

A Suite of Ontologies for Robotics and Automation [Industrial Activities]

Reports on the formation and activities undertaken by the Ontologies for Robotics and Automation (ORA) Working Group. ORA was established in 2011 by the IEEE Standard Associations Robotics Society. The goal of the group is to develop a standard to provide an overall ontology and associated methodology for knowledge representation and reasoning in robotics and automation together with the representation of concepts in an initial set of application domains. The standard provides a unified way of representing knowledge and provides a common set of terms and definitions, allowing for unambiguous knowledge transfer among any group of human, robots, and other artificial systems.

Services integration framework for vehicle telematics

Development of a General Application Framework based on SOA for a Robust Service Platform that can be used in dynamic environments employing Open Systems, Open Standards and Open Source is being proposed here to provide a basis for research and development of complete systems and solutions specifically targeted for Telematic Applications. Example Service Implementations using Telematics and Web Service Techniques illustrate the efficient Service Invocation and interaction in the Service Platform architecture as Service Components and Applications. The Functional, Design and Structural Aspects of the Service Architecture are also described.

Unified modelling framework for UAVs using Bond Graphs

This paper presents a novel unified modelling approach using Bond Graphs (BG) as a graphical language and as a framework for modelling and validation for UAVs. The proposed framework supports a concurrent design approach across the domains. In addition, it doubles as a design and knowledge framework for physical systems at various levels of abstraction. This framework can be used as a tool to facilitate design refinement from behavioural and functional modelling to explore system architecture and for rapid prototyping of mechatronic systems such as UAVs. The model framework was applied to a R-50 experimental model helicopter for obtaining preliminary results.

Waypoint-based path planner for Mobile Robot Navigation using PSO and GA-AIS

Service Robotic application deployments have taken a giant leap in complexity. They have been successfully deployed in wide range of applications from NASA Mars Rovers to domestic lawn mowers. Waypoint Navigation Systems (WNS) can now be used as an alternate Mobile Robot Navigation (MRN) technique with advances in Global Positioning Systems (GPS) and Global Information systems (GIS).Regardless of the application, the path planning and navigation has remained an important part of Mobile Robot application development. This paper presents two optimization algorithms to solve Path Planning Problem for Robot Navigation. The Particle Swarm Optimization (PSO) and Genetic Algorithm - Artificial Immune System (GA-AIS) were developed and implemented for the path optimization (shortest route) and the behavior of these two algorithms has been compared.

PAINTbot - FPGA based wall painting service robot prototype

A fully functional wall painting robot prototype for indoor and outdoor environments has been developed. The prototype development includes building the hardware and software subsystems for the robot. The robot controller has developed using the Altera DE2 Development Board with the software implementation done in Quartus II 8.1 and NIOS II IDE using C language programming. Hardware development of the robot involves building the main chassis, the stepper motor and drivers, sensor circuitries and electro pneumatic controls of the air brush for painting. The software implementation includes converting the MATLAB code to C and VHDL codes to generate the coordinates when the area of the workspace is provided. These coordinates are used to specify the changes in length for the supporting string. The robot movements from point to point are done based on changing the respective suspension lengths to reach a particular coordinate. A path planning algorithm was developed and validated in MATLAB with two path options, z-path and u-path. The paint area was also plotted on the workspace in the GUI. In the functional prototype, the robot is able to paint a workspace specified by user, avoiding all windows area. However, the quality of painting needs to be greatly improved before deployments are possible.

A reconfigurable FPGA framework for data fusion in UAV's.

This paper presents the results of an effort to develop a reconfigurable helicopter platform capable of autonomous flight using a reconfigurable FPGA Framework to fuse the data from sensors, Readings from accelerometer and absolute GPS Location data is fused using Kalman filter to combine the low frequency stability of GPS systems with the high frequency tracking of accelerometers thus achieving stable static and dynamic three-degree-of-freedom tracking for the use of an UAV onboard navigational system. The sensor data can have different data rates and noise figures. Simulation was done on data fusion of noisy GPS and accelerometer data using Kalman filter. The results showed the data fusion of the sensors gives a better positional and velocity estimates decreasing the average errors of positional and velocity estimates by more than 50%. More over the fused data does not accumulate error over time, as compared to positional and velocity estimates obtained earlier.