The Experts below are selected from a list of 11988 Experts worldwide ranked by ideXlab platform
Eric Krotkov - One of the best experts on this subject based on the ideXlab platform.
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ICRA - Dead Reckoning for a lunar rover on uneven terrain
Proceedings of IEEE International Conference on Robotics and Automation, 1996Co-Authors: Y Fuke, Eric KrotkovAbstract:This paper extends the classic Dead Reckoning approach to the case of a mobile robot moving on uneven terrain such as the lunar surface or a construction site. In addition to the wheel encoders employed in classical odometry, the approach uses accelerometer and gyroscopic sensors, routinely used in aviation but rarely found on contemporary mobile robots. The paper derives a complementary Kalman filter that fuses accelerometer and rate gyro data to increase the accuracy of Dead Reckoning on uneven terrain. The paper presents empirical demonstrations on the effectiveness of the new method with mobile robot traverses over crater ground.
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Dead Reckoning for a lunar rover on uneven terrain
International Conference on Robotics and Automation, 1996Co-Authors: Y Fuke, Eric KrotkovAbstract:This paper extends the classic Dead Reckoning approach to the case of a mobile robot moving on uneven terrain such as the lunar surface or a construction site. In addition to the wheel encoders employed in classical odometry, the approach uses accelerometer and gyroscopic sensors, routinely used in aviation but rarely found on contemporary mobile robots. The paper derives a complementary Kalman filter that fuses accelerometer and rate gyro data to increase the accuracy of Dead Reckoning on uneven terrain. The paper presents empirical demonstrations on the effectiveness of the new method with mobile robot traverses over crater ground.
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Stereo perception and Dead Reckoning for a prototype lunar rover
Autonomous Robots, 1995Co-Authors: Eric Krotkov, Martial Hebert, Reid SimmonsAbstract:This paper describes practical, effective approaches to stereo perception and Dead Reckoning, and presents results from systems implemented for a prototype lunar rover operating in natural, outdoor environments.
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IROS - Dead Reckoning Navigation For Walking Robots
Proceedings of the IEEE RSJ International Conference on Intelligent Robots and Systems, 1992Co-Authors: G.p. Roston, Eric KrotkovAbstract:Abstract : Autonomous and teleoperated mobile robots require an accurate knowledge of their spatial location in order to accomplish many tasks. Many mobile robots make use of Dead Reckoning navigation because of its simplicity, low cost and robustness. Although Dead Reckoning navigation has been used for centuries for ships and wheeled vehicles, the application to a walking machine is novel. Since walking machines differ greatly from ships and wheeled vehicles, a new approach to Dead Reckoning was developed to solve this problem. This paper discusses the problem, a solution, preliminary test results and future goals for Dead Reckoning navigation. Experiments were done with the CMU Ambler, an autonomous, six-legged walking robot, but the results are general and apply to any statically stable walking robot. The current results show a systematic bias of two percent of body advance in the direction of travel. Although the cause of this bias is unknown, it is corrected in the position estimation routines.
Philippe Bonnifait - One of the best experts on this subject based on the ideXlab platform.
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Four-Wheeled Dead-Reckoning Model Calibration using RTS Smoothing
2019 International Conference on Robotics and Automation (ICRA), 2019Co-Authors: Anthony Welte, Philippe Xu, Philippe BonnifaitAbstract:Localization is one of the main challenges to be addressed to develop autonomous vehicles able to perform complex maneuvers on roads opened to public traffic. Having an accurate Dead-Reckoning system is an essential step to reach this objective. This paper presents a Dead-Reckoning model for car-like vehicles that performs the data fusion of complementary and redundant sensors: wheel encoders, yaw rate gyro and steering wheel measurements. In order to get an accurate Dead-Reckoning system with a drift reduced to the minimum, the parameters have to be well calibrated and the procedure has to be simple and efficient. We present a method able to accurately calibrate the parameters without knowing the ground truth by using a Rauch-Tung-Striebel smoothing scheme which enables to obtain state estimates as close to the ground truth as possible. The smoothed estimates are then used within a optimization process to calibrate the model parameters. The method has been tested using data recorded from an experimental vehicle on public roads. The results show a significant diminution of the Dead-Reckoning drift compared to a commonly used calibration method. We evaluate finally the average distance a vehicle can navigate without exteroceptive sensors by using the proposed four-wheeled Dead Reckoning system.
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ICRA - Four-Wheeled Dead-Reckoning Model Calibration using RTS Smoothing
2019 International Conference on Robotics and Automation (ICRA), 2019Co-Authors: Anthony Welte, Philippe Xu, Philippe BonnifaitAbstract:Localization is one of the main challenges to be addressed to develop autonomous vehicles able to perform complex maneuvers on roads opened to public traffic. Having an accurate Dead-Reckoning system is an essential step to reach this objective. This paper presents a Dead-Reckoning model for car-like vehicles that performs the data fusion of complementary and redundant sensors: wheel encoders, yaw rate gyro and steering wheel measurements. In order to get an accurate Dead-Reckoning system with a drift reduced to the minimum, the parameters have to be well calibrated and the procedure has to be simple and efficient. We present a method able to accurately calibrate the parameters without knowing the ground truth by using a Rauch-Tung-Striebel smoothing scheme which enables to obtain state estimates as close to the ground truth as possible. The smoothed estimates are then used within a optimization process to calibrate the model parameters. The method has been tested using data recorded from an experimental vehicle on public roads. The results show a significant diminution of the Dead-Reckoning drift compared to a commonly used calibration method. We evaluate finally the average distance a vehicle can navigate without exteroceptive sensors by using the proposed four-wheeled Dead Reckoning system.
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Map-Aided Dead-Reckoning With Lane-Level Maps and Integrity Monitoring
IEEE Transactions on Intelligent Vehicles, 2018Co-Authors: Franck Li, Philippe Bonnifait, Javier Ibañez-guzmánAbstract:Navigation maps provide critical information for advanced driving assistance systems and autonomous vehicles. When these maps are refined to lane-level, ambiguities may occur during the map-matching process, particularly when positioning estimates are inaccurate. This paper presents a Dead-Reckoning method implementing a particle filter to estimate a set of likely map-matched hypotheses containing the correct solution with a high probability. Our method uses lane-level maps that feature dedicated attributes such as connectedness and adjacency. The vehicle position is essentially estimated by Dead-Reckoning sensors and lane detection using an intelligent camera. We also describe an integrity monitoring method for assessing the coherence of the set of hypotheses, using the fix of a global navigation satellite system receiver. The method provides in real-time a “Use/Don't Use” characterization of the vehicle positioning information that is transmitted to safety functions, where integrity is fundamental. The performance of the proposed map-aided Dead-Reckoning method with integrity monitoring is evaluated using data acquired by an experimental car on suburban public roads. The results obtained validate the approach.
Anthony Welte - One of the best experts on this subject based on the ideXlab platform.
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Four-Wheeled Dead-Reckoning Model Calibration using RTS Smoothing
2019 International Conference on Robotics and Automation (ICRA), 2019Co-Authors: Anthony Welte, Philippe Xu, Philippe BonnifaitAbstract:Localization is one of the main challenges to be addressed to develop autonomous vehicles able to perform complex maneuvers on roads opened to public traffic. Having an accurate Dead-Reckoning system is an essential step to reach this objective. This paper presents a Dead-Reckoning model for car-like vehicles that performs the data fusion of complementary and redundant sensors: wheel encoders, yaw rate gyro and steering wheel measurements. In order to get an accurate Dead-Reckoning system with a drift reduced to the minimum, the parameters have to be well calibrated and the procedure has to be simple and efficient. We present a method able to accurately calibrate the parameters without knowing the ground truth by using a Rauch-Tung-Striebel smoothing scheme which enables to obtain state estimates as close to the ground truth as possible. The smoothed estimates are then used within a optimization process to calibrate the model parameters. The method has been tested using data recorded from an experimental vehicle on public roads. The results show a significant diminution of the Dead-Reckoning drift compared to a commonly used calibration method. We evaluate finally the average distance a vehicle can navigate without exteroceptive sensors by using the proposed four-wheeled Dead Reckoning system.
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ICRA - Four-Wheeled Dead-Reckoning Model Calibration using RTS Smoothing
2019 International Conference on Robotics and Automation (ICRA), 2019Co-Authors: Anthony Welte, Philippe Xu, Philippe BonnifaitAbstract:Localization is one of the main challenges to be addressed to develop autonomous vehicles able to perform complex maneuvers on roads opened to public traffic. Having an accurate Dead-Reckoning system is an essential step to reach this objective. This paper presents a Dead-Reckoning model for car-like vehicles that performs the data fusion of complementary and redundant sensors: wheel encoders, yaw rate gyro and steering wheel measurements. In order to get an accurate Dead-Reckoning system with a drift reduced to the minimum, the parameters have to be well calibrated and the procedure has to be simple and efficient. We present a method able to accurately calibrate the parameters without knowing the ground truth by using a Rauch-Tung-Striebel smoothing scheme which enables to obtain state estimates as close to the ground truth as possible. The smoothed estimates are then used within a optimization process to calibrate the model parameters. The method has been tested using data recorded from an experimental vehicle on public roads. The results show a significant diminution of the Dead-Reckoning drift compared to a commonly used calibration method. We evaluate finally the average distance a vehicle can navigate without exteroceptive sensors by using the proposed four-wheeled Dead Reckoning system.
Y Fuke - One of the best experts on this subject based on the ideXlab platform.
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Dead Reckoning for a lunar rover on uneven terrain
International Conference on Robotics and Automation, 1996Co-Authors: Y Fuke, Eric KrotkovAbstract:This paper extends the classic Dead Reckoning approach to the case of a mobile robot moving on uneven terrain such as the lunar surface or a construction site. In addition to the wheel encoders employed in classical odometry, the approach uses accelerometer and gyroscopic sensors, routinely used in aviation but rarely found on contemporary mobile robots. The paper derives a complementary Kalman filter that fuses accelerometer and rate gyro data to increase the accuracy of Dead Reckoning on uneven terrain. The paper presents empirical demonstrations on the effectiveness of the new method with mobile robot traverses over crater ground.
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ICRA - Dead Reckoning for a lunar rover on uneven terrain
Proceedings of IEEE International Conference on Robotics and Automation, 1996Co-Authors: Y Fuke, Eric KrotkovAbstract:This paper extends the classic Dead Reckoning approach to the case of a mobile robot moving on uneven terrain such as the lunar surface or a construction site. In addition to the wheel encoders employed in classical odometry, the approach uses accelerometer and gyroscopic sensors, routinely used in aviation but rarely found on contemporary mobile robots. The paper derives a complementary Kalman filter that fuses accelerometer and rate gyro data to increase the accuracy of Dead Reckoning on uneven terrain. The paper presents empirical demonstrations on the effectiveness of the new method with mobile robot traverses over crater ground.
T.k. Capin - One of the best experts on this subject based on the ideXlab platform.
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A Dead-Reckoning technique for streaming virtual human animation
IEEE Transactions on Circuits and Systems for Video Technology, 1999Co-Authors: T.k. Capin, J. Esmerado, D. ThalmannAbstract:In networked virtual environments (NVEs), users are represented by their virtual embodiments. The articulated structure of these embodiments introduces a new complexity in the representation and streaming of animations, especially when the number of participants in the simulation increases. This requires real-time algorithms to decrease the networking overhead. The Dead-Reckoning technique is a way to reduce the required bit rate, and has been used for simple nonarticulated objects in popular NVE systems. We introduce a Dead-Reckoning technique for articulated virtual human figures, based on the MPEG-4 body animation specification, using Kalman filtering.
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VRAIS - A Dead-Reckoning algorithm for virtual human figures
Proceedings of IEEE 1997 Annual International Symposium on Virtual Reality, 1997Co-Authors: T.k. Capin, Igor S. PandzicAbstract:In networked virtual environments, when the participants are represented by virtual human figures, the articulated structure of the human body introduces a new complexity in the usage of the network resources. This might create a significant overhead in communication, especially as the number of participants in the simulation increases. In addition, the animation should be realistic, as it is easy to recognize anomalies in the virtual human animation. This requires real-time algorithms to decrease the network overhead while considering characteristics of body motion. The Dead-Reckoning technique is a way to decrease the number of messages communicated among the participants, and has been used for simple non-articulated objects in popular systems. The authors introduce a Dead-Reckoning technique for articulated virtual human figures based on Kalman filtering, discuss main issues and present experimental results.
