Natural swarms have inspired various controlling algorithms for swarm robotics, while few of them were programmed in a similar way as the natural swarms. Defining a reliable programming method is still a daunting chal...
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During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintain...
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Autism spectrum disorder (ASD) is a lifelong developmental condition that affects an individual’s ability to communicate and relate to others. Despite such challenges, early intervention during childhood development ...
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Due to the lack of accurate stability theoretical basis, the dynamic balance control of bipedal robots is a challenging topic. In this paper, we propose a controller that combines virtual model control and whole body ...
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Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classifi...
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When a biped robot walks at a high speed, only relying on the open-loop gait trajectory based on the linear inverted pendulum model (LIPM), the robot cannot maintain stability. Sudden contact with the ground when land...
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Inverse Kinematics (IK) is one of the most fundamental challenges in robotics. It refers to the process of determining the joint configurations required to achieve the desired position and orientation (pose) of a robo...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
Inverse Kinematics (IK) is one of the most fundamental challenges in robotics. It refers to the process of determining the joint configurations required to achieve the desired position and orientation (pose) of a robot end-effector. Although numerous Data-Driven (DD) IK solvers have demonstrated encouraging results, they have not achieved the same accuracy when compared to other IK methods for complex robot configurations (e.g., numerical methods for higher Degrees of Freedom (DoF)). In this work, we propose a new Learning-by-Example method, and show that such a scheme considerably improves the IK learning results when compared to other DD learners. In our approach, the network input incorporates an example of joint-pose pair along with the query pose to predict the desired robot joint configuration. We show that the example joint-pose pair does not need to be too close to the query – i.e. example and query can be as far as 20 degrees apart in the joint configuration space. Furthermore, we investigate the utilization of residual and dense skip connections in Multilayer Perceptron for DDIK solvers and employ the resulting networks for two redundant robotic manipulators: a 7-DoF-7R commensurate robot and a 7DoF-2RP4R incommensurate robot. Our experimental results show that the resulting DDIK solver can reliably predict IK solutions with accuracy better than 1mm in position and 1deg in orientation.
In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the curr...
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In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.
In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the la...
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In human-robot interaction (HRI), human pose estimation is a necessary technology for the robot to perceive the dynamic environment and make interactive actions. Recently, graph convolutional networks (GCNs) have been...
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