To locate the object accurately in a scene for further vision processing, a novel bio-inspired model for image segmentation is proposed, which closely follows the computation of trickle-up and trickle-down processing ...
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A Norm-Optimal Iterative Learning Control (NOILC) solution is developed for the problem when tracking is only required at a subset of isolated time points along the trial duration. Well-defined convergence properties ...
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A new control scheme for position-orientation tracking of underactuated quadrotor robotic vehicle is proposed. A quaternion-based sliding surface parametrizes the open-loop error equation of orientation dynamics, then...
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ISBN:
(纸本)9781457710957
A new control scheme for position-orientation tracking of underactuated quadrotor robotic vehicle is proposed. A quaternion-based sliding surface parametrizes the open-loop error equation of orientation dynamics, then a second order sliding mode (SOSM) is synthesized for global exponential stabilization of attitude coordinates along an orientation equilibrium manifold. This SOSM for any initial condition leads to a simplified design of a torque PD controller for position dynamics, for globally uniformly ultimately bounded of position trajectories. The SOSM reacts to the effect of the PD as if it were an endogenous persistent disturbance, which vanishes until it reaches its equilibrium position manifold. In contrast to other results that consider the full model without linearization nor further simplifications, our proposal yields a controller which is smooth and does not require the dynamic model. Since the parametrization of attitude representation is global, aggressive maneuvering capabilities are exhibited. Simulations are presented for a variety of flight regimes, including carry out helixes and loops at high angular velocities. Real-time experiments provide a glimpse of the closed-loop performance for a custom made quadrotor.
The effective operation of service robots relies on developmental programs that allow the robot to expand its knowledge about its dynamic operating environment. Motivation theories from neuroscience and neuropsycholog...
The effective operation of service robots relies on developmental programs that allow the robot to expand its knowledge about its dynamic operating environment. Motivation theories from neuroscience and neuropsychology study the underlying mechanisms that drive the engagement of biological creatures to certain activities, such as learning. This research uses a physical Willow Garage PR2 robot, which is equipped with a cumulative learning mechanism driven by the intrinsic motivation of novelty detection based on computational models of biological habituation. It cumulatively learns the 360° appearance of novel real-world objects by picking them up. This paper discusses the theoretical motivations and background information on intrinsic motivations as novelty detection. The results and conclusions from the experimental study are presented.
This paper presents the age-group classification based on facial images. We perform age-group classification by dividing ages into five age groups according to the incremental regulation of age. Features are extracted...
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This paper presents the age-group classification based on facial images. We perform age-group classification by dividing ages into five age groups according to the incremental regulation of age. Features are extracted from face images through Active Appearance Model (AAM), which describe the shape and gray value variation of face images. Principle Component Analysis (PCA) is adopted to reduce the dimensions and Support Vector Machine (SVM) classifier with Gaussian Radian Basis Function (RBF) kernel is trained. Experimental results demonstrate that AAM can improve the performance of age estimation.
Micro Aerial Vehicles (MAVs) have gained a significant amount of research lately, with a number of universities and industry sponsors paving the way with micro flying robots to perform Intelligence, Surveillance and R...
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ISBN:
(纸本)9781612843858
Micro Aerial Vehicles (MAVs) have gained a significant amount of research lately, with a number of universities and industry sponsors paving the way with micro flying robots to perform Intelligence, Surveillance and Reconnaissance (ISR) Missions. However, much of the work done in flapping wing MAVs till date has not shown performance improvements over their Vertical Take Off and Landing (VTOL), rotary-wing counterparts. Research and development over the years has shown that insects and birds have unmatched flying capabilities in the Low Reynolds Number Regime. Their phenomenal flight performance is attributed to among others the highly energy efficient actuation systems and their power to weight ratios. The paper proposes and illustrates new and energy-efficient actuation mechanisms and incorporating them into MAVs. The paper begins by elaborating on the background of our research and the need for energy efficiency in MAVs;followed by showcasing resonant, elastic/restorative actuation mechanisms and their control methodology to reduce flight-actuation energy requirements. In conclusion, the paper contrasts and compares all the actuation systems for power intake, scalability and mechanical complexity.
Wireless sensor networks (WSNs) have attracted a great deal of research due to their wide-range of potential applications. Sensor deployment and coverage problems are their important issues. This article briefly intro...
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This paper proposes a general learning framework for robots to learn behaviors through imitation and interaction. A modified codebook based method is used for robots to segment and recognize new objects in the environ...
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This paper proposes a general learning framework for robots to learn behaviors through imitation and interaction. A modified codebook based method is used for robots to segment and recognize new objects in the environment. Task related semantic information is learned by robots through the speech communication with humans. Dynamic Movement Primitive method is used to generate similar behaviors to complete similar but slightly different tasks. Experimental results are given to verify the effectiveness of this framework.
In order to approach human hand performance levels, artificial anthropomorphic hands/fingers have increasingly incorporated human biomechanical features. However, the performance of finger reaching movements to visual...
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ISBN:
(纸本)9781424441198
In order to approach human hand performance levels, artificial anthropomorphic hands/fingers have increasingly incorporated human biomechanical features. However, the performance of finger reaching movements to visual targets involving the complex kinematics of multijointed, anthropomorphic actuators is a difficult problem. This is because the relationship between sensory and motor coordinates is highly nonlinear, and also often includes mechanical coupling of the two last joints. Recently, we developed a cortical model that learns the inverse kinematics of a simulated anthropomorphic finger. Here, we expand this previous work by assessing if this cortical model is able to learn the inverse kinematics for an actual anthropomorphic humanoid finger having its two last joints coupled and controlled by pneumatic muscles. The findings revealed that single 3D reaching movements, as well as more complex patterns of motion of the humanoid finger, were accurately and robustly performed by this cortical model while producing kinematics comparable to those of humans. This work contributes to the development of a bioinspired controller providing adaptive, robust and flexible control of dexterous robotic and prosthetic hands.
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