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Kira, Zsolt

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Author: Arkin, Ronald C. × Type: Text ×

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Now showing 1 - 4 of 4
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    A Design Process for Robot Capabilities and Missions Applied to Microautonomous Platforms
    (Georgia Institute of Technology, 2010) Kira, Zsolt ; Arkin, Ronald C. ; Collins, Thomas R.
    As part of our research for the ARL MAST CTA (Collaborative Technology Alliance) [1], we present an integrated architecture that facilitates the design of microautonomous robot platforms and missions, starting from initial design conception to actual deployment. The framework consists of four major components: design tools, mission-specification system (MissionLab), case-based reasoning system (CBR Expert), and a simulation environment (USARSim). The designer begins by using design tools to generate a space of missions, taking broad mission-specific objectives into account. For example, in a multi-robot reconnaissance task, the parameters varied include the number of robots used, mobility capabilities (e.g. maximum speeds), and sensor capabilities. The design tools are used to intelligently carve out the space of all possible parameter combinations to produce a smaller set of mission configurations. Quantitative assessment of this design space is then performed in simulation to determine which particular configuration would yield an effective team before actual deployment. MissionLab, a mission-specification platform, is used to incorporate the input parameters, generate the underlying robot missions, and control the robots in simulation. It also provides logging mechanisms to measure a range of quantitative performance metrics, such as mission completion rates, resource utilization, and time to completion, which are then used to determine the best configuration for a particular mission. These metrics can also provide guidance for the refinement of the entire design process. Finally, a case-based reasoning system allows users to maximize successful deployment of the robots by retrieving proven configurations and determine the robot capabilities necessary for success in a particular mission.
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    Mission Specification and Control for Unmanned Aerial and Ground Vehicles for Indoor Target Discovery and Tracking
    (Georgia Institute of Technology, 2010) Ulam, Patrick D. ; Kira, Zsolt ; Arkin, Ronald C. ; Collins, Thomas R.
    This paper describes ongoing research by Georgia Tech into the challenges of tasking and controlling heterogonous teams of unmanned vehicles in mixed indoor/outdoor reconnaissance scenarios. We outline the tools and techniques necessary for an operator to specify, execute, and monitor such missions. The mission specification framework used for the purposes of intelligence gathering during mission execution are first demonstrated in simulations involving a team of a single autonomous rotorcraft and three ground-based robotic platforms. Preliminary results including robotic hardware in the loop are also provided.
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    Spatio-Temporal Case-Based Reasoning for Efficient Reactive Robot Navigation
    (Georgia Institute of Technology, 2005) Likhachev, Maxim ; Kaess, Michael ; Kira, Zsolt ; Arkin, Ronald C.
    This paper presents an approach to automatic selection and modification of behavioral assemblage parameters for autonomous navigation tasks. The goal of this research is to make obsolete the task of manual configuration of behavioral parameters, which often requires significant knowledge of robot behavior and extensive experimentation, and to increase the efficiency of robot navigation by automatically choosing and fine-tuning the parameters that fit the robot task-environment well in real-time. The method is based on the Case-Based Reasoning paradigm. Derived from incoming sensor data, this approach computes spatial features of the environment. Based on the robot’s performance, temporal features of the environment are then computed. Both sets of features are then used to select and fine-tune a set of parameters for an active behavioral assemblage. By continuously monitoring the sensor data and performance of the robot, the method reselects these parameters as necessary. While a mapping from environmental features onto behavioral parameters, i.e., the cases, can be hard-coded, a method for learning new and optimizing existing cases is also presented. This completely automates the process of behavioral parameterization. The system was integrated within a hybrid robot architecture and extensively evaluated using simulations and indoor and outdoor real world robotic experiments in multiple environments and sensor modalities, clearly demonstrating the benefits of the approach.
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    Forgetting Bad Behavior: Memory Management for Case-Based Navigation
    (Georgia Institute of Technology, 2004) Kira, Zsolt ; Arkin, Ronald C.
    In this paper, we present successful strategies for forgetting cases in a Case-Based Reasoning (CBR) system applied to autonomous robot navigation. This extends previous work that involved a CBR architecture which indexes cases by the spatio-temporal characteristics of the sensor data, and outputs or selects parameters of behaviors in a behavior-based robot architecture. In such a system, the removal of cases can be applied when a new situation unlike any current case in the library is encountered, but the library is full. Various strategies of determining which cases to remove are proposed, including metrics such as how frequently a case is used and a novel spreading activation mechanism. Experimental results show that such mechanisms can increase the performance of the system significantly and allow it to essentially forget old environments in which it was trained in favor of new environments it is currently encountering. The performance of this new system is better than both a purely reactive behavior-based system as well as the CBR module that did not forget cases. Furthermore, such forgetting mechanisms can be useful even when there is no major environmental shift during training, since some cases can potentially be harmful or rarely used. The relationship between the forgetting mechanism and the case library size is also discussed.