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| 2. |
- Ishigami, Genya, et al.
(författare)
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Statistical Approach to Mobility Prediction for Planetary Surface Exploration Rovers in Uncertain Terrain
- 2009
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Ingår i: IEEE robotics & automation magazine. - Piscataway, N.J. : IEEE Press. - 1070-9932 .- 1558-223X. ; 16:4, s. 61-70, s. 588-593
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Tidskriftsartikel (refereegranskat)abstract
- Planetary surface exploration rovers must accurately and efficiently predict their mobility on natural, rough terrain. Most approaches to mobility prediction assume precise a priori knowledge of terrain physical parameters, however in practical scenarios knowledge of terrain parameters contains significant uncertainty. In this paper, a statistical method for mobility prediction that incorporates terrain uncertainty is presented. The proposed method consists of two techniques: a wheeled vehicle model for calculating vehicle dynamic motion and wheel-terrain interaction forces, and a stochastic response surface method (SRSM) for modeling of uncertainty. The proposed method generates a predicted motion path of the rover with confidence ellipses indicating the probable rover position due to uncertainty in terrain physical parameters. Rover orientations and wheel slippage are also predicted. The computational efficiency of SRSM as compared to conventional Monte Carlo methods is shown via numerical simulations. Experimental results of rover travel over sloped terrain in two different uncertain terrains are presented that confirms the utility of the proposed mobility prediction method. ©2010 IEEE.
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| 3. |
- Kewlani, Gaurav, et al.
(författare)
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A Multi-Element Generalized Polynomial Chaos Approach to Analysis of Mobile Robot Dynamics under Uncertainty
- 2009
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Ingår i: IROS 2009. - Piscataway, N.J. : IEEE Robotics and Automation Society. ; , s. 1177-1182
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Konferensbidrag (refereegranskat)abstract
- The ability of mobile robots to quickly and accurately analyze their dynamics is critical to their safety and efficient operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this must be considered in an analysis of robot motion. Here a Multi-Element generalized Polynomial Chaos (MEgPC) approach is presented that explicitly considers vehicle parameter uncertainty for long term estimation of robot dynamics. It is shown to be an improvement over the generalized Askey polynomial chaos framework as well as the standard Monte Carlo scheme, and can be used for efficient, accurate prediction of robot dynamics. © 2009 IEEE.
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| 5. |
- Kewlani, Gaurav, et al.
(författare)
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A Stochastic Response Surface Approach to Statistical Prediction of Mobile Robot Mobility
- 2008
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Ingår i: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). - Piscataway, N.J. : IEEE Press. ; , s. 2234-2239
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Konferensbidrag (refereegranskat)abstract
- The ability of autonomous or semi-autonomous mobile robots to rapidly and accurately predict their mobility characteristics is an important requirement for their use in unstructured environments. Most methods for mobility prediction, however, assume precise knowledge of environmental (i.e. terrain) properties. In practical conditions, significant uncertainty is associated with terrain parameter estimation from robotic sensors, and this uncertainty must be considered in a mobility prediction algorithm. Here a method for efficient mobility prediction based on the stochastic response surface approach is presented that explicitly considers terrain parameter uncertainty. The method is compared to a Monte Carlo-based method and simulations show that the stochastic response surface approach can be used for efficient, accurate prediction of mobile robot mobility. ©2008 IEEE.
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| 6. |
- Kewlani, Gaurav, et al.
(författare)
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Mobility prediction for unmanned ground vehicles in uncertain environments
- 2008
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Ingår i: Unmanned systems technology X. - Bellingham, WA : SPIE - International Society for Optical Engineering. - 9780819471536 ; , s. Article number 69621G-
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Konferensbidrag (refereegranskat)abstract
- The ability of autonomous unmanned ground vehicles (UGVs) to rapidly and effectively predict terrain negotiability is a critical requirement for their use on challenging terrain. Most methods for assessing traversability, however, assume precise knowledge of vehicle and terrain properties. In practical applications, uncertainties are associated with the estimation of the vehicle/terrain parameters, and these uncertainties must be considered while determining vehicular mobility. Here a computationally inexpensive method for efficient mobility prediction based on the stochastic response surface (SRSM) approach is presented that considers imprecise knowledge of terrain and vehicle parameters while analyzing various metrics associated with UGV mobility. A conventional Monte Carlo method and the proposed response surface methodology have been applied to two simulated cases of mobility analysis, and it has been shown that the SRSM method is an efficient tool as compared to conventional Monte Carlo methods for the analysis of vehicular mobility in uncertain environments.
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| 7. |
- Kewlani, Gaurav, et al.
(författare)
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Stochastic Mobility-based Path Planning in Uncertain Environments
- 2009
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Ingår i: IROS 2009. - Piscataway, N.J. : IEEE Press. - 9781424438044 ; , s. 1183-1189
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Konferensbidrag (refereegranskat)abstract
- The ability of mobile robots to generate feasible trajectories online is an important requirement for their autonomous operation in unstructured environments. Many path generation techniques focus on generation of time- or distance-optimal paths while obeying dynamic constraints, and often assume precise knowledge of robot and/or environmental (i.e. terrain) properties. In uneven terrain, it is essential that the robot mobility over the terrain be explicitly considered in the planning process. Further, since significant uncertainty is often associated with robot and/or terrain parameter knowledge, this should also be accounted for in a path generation algorithm. Here, extensions to the rapidly exploring random tree (RRT) algorithm are presented that explicitly consider robot mobility and robot parameter uncertainty based on the stochastic response surface method (SRSM). Simulation results suggest that the proposed approach can be used for generating safe paths on uncertain, uneven terrain. © 2009 IEEE.
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| 9. |
- Rohde, Mitchell M., et al.
(författare)
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An Interactive, physics-based unmanned ground vehicle simulator leveraging open source gaming technology : Progress in the development and application of the virtual autonomous navigation environment (VANE) desktop
- 2009
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Ingår i: Unmanned Systems Technology XI. - Bellingham, WA : SPIE - International Society for Optical Engineering. - 9780819475985 ; , s. Article number 73321C-
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Konferensbidrag (refereegranskat)abstract
- It is widely recognized that simulation is pivotal to vehicle development, whether manned or unmanned. There are few dedicated choices, however, for those wishing to perform realistic, end-to-end simulations of unmanned ground vehicles (UGVs). The Virtual Autonomous Navigation Environment (VANE), under development by US Army Engineer Research and Development Center (ERDC), provides such capabilities but utilizes a High Performance Computing (HPC) Computational Testbed (CTB) and is not intended for on-line, real-time performance. A product of the VANE HPC research is a real-time desktop simulation application under development by the authors that provides a portal into the HPC environment as well as interaction with wider-scope semi-automated force simulations (e.g. OneSAF). This VANE desktop application, dubbed the Autonomous Navigation Virtual Environment Laboratory (ANVEL), enables analysis and testing of autonomous vehicle dynamics and terrain/obstacle interaction in real-time with the capability to interact within the HPC constructive geo-environmental CTB for high fidelity sensor evaluations. ANVEL leverages rigorous physics-based vehicle and vehicle-terrain interaction models in conjunction with high-quality, multimedia visualization techniques to form an intuitive, accurate engineering tool. The system provides an adaptable and customizable simulation platform that allows developers a controlled, repeatable testbed for advanced simulations. ANVEL leverages several key technologies not common to traditional engineering simulators, including techniques from the commercial video-game industry. These enable ANVEL to run on inexpensive commercial, off-the-shelf (COTS) hardware. In this paper, the authors d escribe key aspects of ANVEL and its development, as well as several initial applications of the system. © 2009 SPIE.
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