We present a novel visual SLAM method for the warehouse robot with a single downward-facing camera using ground textures. Traditional methods resort to feature matching or point registration for pose optimization, whi...
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All‐solid‐state sodium batteries (ASSSBs) with nonflammable electrolytes and ubiquitous sodium resource are a promising solution to the safety and cost concerns for lithium‐ion batteries. However, the intrinsic mis...
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All‐solid‐state sodium batteries (ASSSBs) with nonflammable electrolytes and ubiquitous sodium resource are a promising solution to the safety and cost concerns for lithium‐ion batteries. However, the intrinsic mismatch between low anodic decomposition potential of superionic sulfide electrolytes and high operating potentials of sodium‐ion cathodes leads to a volatile cathode–electrolyte interface and undesirable cell performance. Here we report a high‐capacity organic cathode, Na 4 C 6 O 6 , that is chemically and electrochemically compatible with sulfide electrolytes. A bulk‐type ASSSB shows high specific capacity (184 mAh g −1 ) and one of the highest specific energies (395 Wh kg −1 ) among intercalation compound‐based ASSSBs. The capacity retentions of 76 % after 100 cycles at 0.1 C and 70 % after 400 cycles at 0.2 C represent the record stability for ASSSBs. Additionally, Na 4 C 6 O 6 functions as a capable anode material, enabling a symmetric all‐organic ASSSB with Na 4 C 6 O 6 as both cathode and anode materials.
We employ recent control design algorithms for delay systems to address the mixed sensitivity design of a dynamic controller for multiple degree of freedom systems interconnected with an inverse signal shaper. A delay...
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This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitab...
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This paper proposes a method of vision based pose estimation of randomly piled objects. It is necessary to estimate precise rotation angle of picking objects. However, it is non-trivial task because an object placed i...
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This paper proposes a method of vision based pose estimation of randomly piled objects. It is necessary to estimate precise rotation angle of picking objects. However, it is non-trivial task because an object placed in every position makes distorted image far from right position image. We propose a precise pose estimation method of bin picking objects. The landmark feature of a picking object is extracted and is used to estimate coarse rotation angle of object. The pose of the object can be precisely estimated by analyzing feature blobs in the landmark. We have experimented to evaluate proposed method in the pilot system, which is constructed like a real manufacturing environment. The experiments have been conducted using 1,000 images. As a result, the pose estimation accuracy of less than 0.154 degree has obtained.
A system for automatic detection of road damages is essential for logistics management. At the core of the system lies an algorithm for classification of damages. This work intends to establish such an algorithm. In t...
A system for automatic detection of road damages is essential for logistics management. At the core of the system lies an algorithm for classification of damages. This work intends to establish such an algorithm. In the current proposal, the algorithm receives data of the probe vehicle rate of rotations, extracts statistics descriptive from the data to produce a feature vector, and finally, feeds the vector to a simple-three-layer neural network to classify the damages. The types of damages are limited to four cases: normal, pothole, speed bump, and expansion joint. For the development, a probe vehicle is used to produce 400 empirical data involving those four damage cases. By using Monte Carlo approach, the established neural network model is evaluated. The results show that the approach is able to classify the cases with 85% accuracy. The study also finds that the rates of pitch and roll to be the determining factors.
The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operati...
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ISBN:
(纸本)9781509045839
The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this paper we present a principled nonlinear guidance strategy, addressing this problem. More broadly, we propose a methodology for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.
Strong story interactive narratives (IN) are stories that branch based on participant actions where all branches conform to a set of predefined constraints. However, participants in these systems may create branches w...
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