In this paper, we propose an efficient continuous-time LiDAR-Inertial-Camera Odometry, utilizing non-uniform B-splines to tightly couple measurements from the LiDAR, IMU, and camera. In contrast to uniform B-spline-ba...
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A modified output error method (MOEM) for model reference adaptive control (MRAC) and identification (MRAI) is introduced. The regressors are properly chosen so that the open-loop system can be compactly expressed as ...
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A modified output error method (MOEM) for model reference adaptive control (MRAC) and identification (MRAI) is introduced. The regressors are properly chosen so that the open-loop system can be compactly expressed as a stable system with an input linear with respect to the unknown plant parameters. The output error satisfies a constructible stable filtered equation. The method does not require any strictly positive real or arbitrary stable filterings, and the uncertainty on the magnitude of the high-frequency gain of the plant does not result in an overparameterization of the identifier. Sufficient conditions on the reference input under which the parameter and output errors converge exponentially to zero are also given.< >
A benchmark study of two self-organizing artificial neural network models, ART2 and DIGNET, is conducted. The architecture differences and learning procedures between these two models are compared. The performance of ...
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A benchmark study of two self-organizing artificial neural network models, ART2 and DIGNET, is conducted. The architecture differences and learning procedures between these two models are compared. The performance of ART2 and DIGNET on data clustering and signal detection problems with noise or interference is investigated by comparative simulations. It is shown that DIGNET generally has faster learning and better clustering performance on the statistical pattern recognition problems. DIGNET has a simpler architecture, and the system parameters can be analytically determined from the self-organizing process. The threshold value used in DIGNET can be specifically determined from a given lower bound on the desirable signal-to-noise ratio (SNR). The networks discussed in this paper are applied and benchmarked against clustering and signal detection problems.
The process of identifying key information in unstructured sets of textual information is complex and multiple-aspect. In this regard various methods and technologies are being actively developed that can improve the ...
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Easy, reliable and fast learning from demonstration approaches are desirable for task automation in construction sites. Unlike in classic assembly industry where the robot acts in a well-controlled setting, constructi...
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ISBN:
(数字)9798350376364
ISBN:
(纸本)9798350376371
Easy, reliable and fast learning from demonstration approaches are desirable for task automation in construction sites. Unlike in classic assembly industry where the robot acts in a well-controlled setting, construction sites are unstructured and constantly changing environments. Therefore both workers and robots have to easily adapt to new working scenarios. In this paper we propose a method for automating the joint filling with mastic using a single human demonstration. The demonstration is performed by a human via teleoperation. The learning phase aims at estimating the appropriate tuning parameters of the admittance controller used to reproduce the human motion. Early stage laboratory testings presented in this document demonstrate the validity of the proposed learning scheme.
Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorith...
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Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorithm so as to exploit special features of the hardware and avoid associated architecture shortcomings. This paper presents an investigation into the analysis and design mechanisms that will lead to reduction in the execution time in implementing real-time control algorithms. The proposed mechanisms are exemplified by means of one algorithm, which demonstrates their applicability to real-time applications. An active vibration control （AVC） algorithm for a flexible beam system simulated using the finite difference （FD） method is considered to demonstrate the effectiveness of the proposed methods. A comparative performance evaluation of the proposed design mechanisms is presented and discussed through a set of experiments.
An effective method for neural network based visual pattern recognition is presented. It is shown that it can be successfully used for visual recognition of deformed letters. The main advantages of the presented metho...
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An effective method for neural network based visual pattern recognition is presented. It is shown that it can be successfully used for visual recognition of deformed letters. The main advantages of the presented method are its intuitive appeal, simple implementation and analytical justification.< >
Most of the applications envisioned for micro air vehicles require an on-board E(MR camera. It is only natural to investigate using the on-board camera as a sensor for navigation, guidance, and control. This paper inv...
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ISBN:
(纸本)1563479044
Most of the applications envisioned for micro air vehicles require an on-board E(MR camera. It is only natural to investigate using the on-board camera as a sensor for navigation, guidance, and control. This paper investigates the use of an EO/IR sensor as a seeker in a proportional navigation guidance law for micro air vehicles. Proportional navigation strategies require knowledge of the line-of-site rates and range rate between the vehicle and the target. This paper demonstrates how these quantities can be derived from pixel-specific information provided by an EO/IR sensor. The guidance laws are developed for gimbaled and strapdown sensors on both skid-to-turn and bank-to-turn MAV kinematic models.
We study the problem of finding the minimum-length curvature constrained closed path through a set of regions in the plane. This problem is referred to as the Dubins Traveling Salesperson Problem with Neighborhoods (D...
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We study the problem of finding the minimum-length curvature constrained closed path through a set of regions in the plane. This problem is referred to as the Dubins Traveling Salesperson Problem with Neighborhoods (DTSPN). Two algorithms are presented that transform this infinite dimensional combinatorial optimization problem into a finite dimensional asymmetric TSP by sampling and applying the appropriate transformations, thus allowing the use of existing approximation algorithms. We show for the case of disjoint regions, the first algorithm needs only to sample each region once to produce a tour within a factor of the length of the optimal tour that is independent of the number of regions. We present a second algorithm that performs no worse than the best existing algorithm and can perform significantly better when the regions overlap.
The descriptor observer approach is improved further to a more suitable observer scheme which is applicable to a more general group of faults and systems. Also a disturbance decoupling scheme is added to the mentioned...
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The descriptor observer approach is improved further to a more suitable observer scheme which is applicable to a more general group of faults and systems. Also a disturbance decoupling scheme is added to the mentioned observer in order to enable the observer to distinguish faults from disturbances.
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