Stephen B. Balakirsky

USARSim: a robot simulator for research and education

This paper presents USARSim, an open source high fidelity robot simulator that can be used both for research and education. USARSim offers many characteristics that differentiate it from most existing simulators. Most notably, it constitutes the simulation engine used to run the virtual robots competition within the Robocup initiative. We describe its general architecture, describe examples of utilization, and provide a comprehensive overview for those interested in robot simulations for education, research and competitions.

Bridging the Gap Between Simulation and Reality in Urban Search and Rescue

Research efforts in urban search and rescue grew tremendously in recent years. In this paper we illustrate a simulation software that aims to be the meeting point between the communities of researchers involved in robotics and multi-agent systems. The proposed system allows the realistic modeling of robots, sensors and actuators, as well as complex unstructured dynamic environments. Multiple heterogeneous agents can be concurrently spawned inside the environment. We explain how different sensors and actuators have been added to the system and show how a seamless migration of code between real and simulated robots is possible. Quantitative results supporting the validation of simulation accuracy are also presented.

Towards heterogeneous robot teams for disaster mitigation: Results and performance metrics from RoboCup rescue

There are disclosed benzothiadiazinyl and quinazolinyl substituted carboxylalkyl dipeptides, wherein the benzothiodiazinyl or quinazolinyl portions are joined to the dipeptide portions by an aminocarbonyl group. Compounds of this invention are useful as antihypertensive agents, in the treatment of congestive heart failure and in the treatment of glaucoma. In addition, compounds of this invention have diuretic activity.

Robot simulation physics validation

Computer simulation of robot performance is an essential tool for the development of robot software. In order for simulation results to be valid for implementation on real hardware, the accuracy of the simulation model must be verified. If developers use a robot model that is not similar enough to the actual robot, then their results can be meaningless. To ensure the validity of the robot models, NIST proposes standardized test methods that can be easily replicated in both computer simulation and physical form. The actual robot can be tested, and the computer model can be finely tuned to replicate similar performances on equivalent tests. To illustrate this, we have accomplished this task with the Talon Robot on NIST standard test methods.

An IEEE standard Ontology for Robotics and Automation

This article discusses a newly formed IEEE-RAS working group entitled Ontologies for Robotics and Automation (ORA). The goal of this working group is to develop a standard 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 humans, robots, and other artificial systems. In addition to describing the goal and structure of the group, this article gives some examples of how the ontology, once developed, can be used by applications such as industrial kitting.

Evaluating maps produced by urban search and rescue robots: lessons learned from RoboCup

This paper presents the map evaluation methodology developed for the Virtual Robots Rescue competition held as part of RoboCup. The procedure aims to evaluate the quality of maps produced by multi-robot systems with respect to a number of factors, including usability, exploration, annotation and other aspects relevant to robots and first responders. In addition to the design choices, we illustrate practical examples of maps and scores coming from the latest RoboCup contest, outlining strengths and weaknesses of our modus operandi. We also show how a benchmarking methodology developed for a simulation testbed effortlessly and faithfully transfers to maps built by a real robot. A number of conclusions may be derived from the experience reported in this paper and a thorough discussion is offered.

Design and validation of a Whegs robot in USARSim

Simulation of robots and other vehicles in a virtual domain has multiple benefits. End users can employ the simulation as a training tool to increase their familiarity and skill with the vehicle without risking damage to the robot, potential bystanders, or the surrounding environment. Simulation allows researchers and developers to benchmark the robots performance in a range of scenarios without needing to physically have the robot and or necessary environment(s) present. Beyond benchmarking current designs, researchers and developers can use the information gathered in the simulation to guide and generate new design concepts. USARSim (Urban Search and Rescue Simulation) is a high fidelity simulation tool that is being used to accomplish these goals within the realm of search and rescue. One particular family of robots that can benefit from simulation in the USARSim environment is the Whegs#8482; series of robots developed in the Biologically Inspired Robotics Laboratory at Case Western Reserve University. Whegs robots are highly mobile ground vehicles that use abstracted biological principles to achieve a robust level of terrestrial locomotion. This paper describes a Whegs robot model that was designed and added to USARSims current array of robots. The model was configured to exhibit the same kind of behavioral characteristics found in the real Whegs vehicles. Once these traits were implemented, a preliminary validation study was performed to ensure that the robot interacted with its environment in the same way that the real-life robot would.

Ontology-based methods for enhancing autonomous vehicle path planning

Abstract We report the results of a first implementation demonstrating the use of an ontology to support reasoning about obstacles to improve the capabilities and performance of on-board route planning for autonomous vehicles. This is part of an overall effort to evaluate the performance of ontologies in different components of an autonomous vehicle within the 4D/RCS system architecture developed at NIST. Our initial focus has been on simple roadway driving scenarios where the controlled vehicle encounters potential obstacles in its path. As reported elsewhere [C. Schlenoff, S. Balakirsky, M. Uschold, R. Provine, S. Smith, Using ontologies to aid navigation planning in autonomous vehicles, Knowledge Engineering Review 18 (3) (2004) 243–255], our approach is to develop an ontology of objects in the environment, in conjunction with rules for estimating the damage that would be incurred by collisions with different objects in different situations. Automated reasoning is used to estimate collision damage; this information is fed to the route planner to help it decide whether to plan to avoid the object. We describe the results of the first implementation that integrates the ontology, the reasoner and the planner. We describe our insights and lessons learned and discuss resulting changes to our approach.

An industrial robotic knowledge representation for kit building applications

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 Industrial Robots sub-group is tasked with studying industrial applications of the ontology. One of the first areas of interest for this subgroup is the area of kit building or kitting. This is a process that brings parts that will be used in assembly operations together in a kit and then moves the kit to the assembly area where the parts are used in the final assembly. This paper examines the knowledge representations that have been developed and implemented for the kitting problem.

Using ontologies to aid navigation planning in autonomous vehicles

This paper explores the hypothesis that ontologies can be used to improve the capabilities and performance of on-board route planning for autonomous vehicles. We name a variety of general benefits that ontologies may provide, and list numerous specific ways that ontologies may be used in different components of our chosen infrastructure: the 4D/RCS system architecture developed at NIST. Our initial focus is on simple roadway driving scenarios where the controlled vehicle encounters objects in its path. Our approach is to develop an ontology of objects in the environment, in conjunction with rules for estimating the damage that would be incurred by collisions with the different objects in different situations. Automated reasoning is used to estimate collision damage; this information is fed to the route planner to help it decide whether to avoid the object. We describe our current experiments and plans for future work.