The performance of multi-robot systems heavily relies on efficient task allocation and motion coordination. However, for a group of a large number of robots, finding the optimal solution is inevitably time-consuming a...
Autonomous underwater vehicles (AUVs) are specialized robots that are commonly used for seafloor surveying and ocean water sampling. computational design approaches have emerged to reduce the effort required to design...
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ISBN:
(纸本)9781728196817
Autonomous underwater vehicles (AUVs) are specialized robots that are commonly used for seafloor surveying and ocean water sampling. computational design approaches have emerged to reduce the effort required to design both individual AUVs as well as fleets. As the number and scale of underwater missions increases beyond the capabilities of a single vehicle, fleet level design will become more important. Depending on the mission, the optimal fleet may consist of multiple distinct types of AUVs designed to a variety of specifications. Moreover, the AUVs may differ in both continuous parameters (such as battery capacity) and discrete parameters (such as number and model of thrusters). In this work, we present a computational pipeline for designing these heterogeneous AUV fleets. Using a novel shape design space based on a graph grammar and deformation cages, we can express a variety of AUV architectures with different topologies, component selections, and dimensions. We search this space using a combination of discrete graph search and gradientbased continuous optimization, enabled by a differentiable AUV simulator. Finally, we formulate heterogeneous fleet design as a modified knapsack problem, and solve it using an efficient backtracking-based algorithm. We evaluate our pipeline on a simulated mission with nonuniform design requirements-surveying a section of seafloor with varying depth-and show that the best heterogeneous fleet outperforms the best fleet composed of a single vehicle type.
In Wireless Rechargeable Sensor Networks (WRSNs), efficient energy management is crucial for prolonging network lifetime. Mobile Charging Vehicles (MCVs) play a vital role in replenishing the energy of sensor nodes (S...
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This paper presents a Non-Linear Model Predictive Controller for humanoid robot locomotion with online step adjustment capabilities. The proposed controller considers the Centroidal Dynamics of the system to compute t...
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ISBN:
(纸本)9781728196817
This paper presents a Non-Linear Model Predictive Controller for humanoid robot locomotion with online step adjustment capabilities. The proposed controller considers the Centroidal Dynamics of the system to compute the desired contact forces and torques and contact locations. Differently from bipedal walking architectures based on simplified models, the presented approach considers the reduced centroidal model, thus allowing the robot to perform highly dynamic movements while keeping the control problem still treatable online. We show that the proposed controller can automatically adjust the contact location both in single and double support phases. The overall approach is then tested with a simulation of one-leg and two-leg systems performing jumping and running tasks, respectively. We finally validate the proposed controller on the position-controlled Humanoid Robot iCub. Results show that the proposed strategy prevents the robot from falling while walking and pushed with external forces up to 40 Newton for 1 second applied at the robot arm.
Natural Language Inference (NLI) is a branch of Natural Language Processing (NLP) whose main task is to determine the relationship between two sentences. Such tasks essentially use pre-trained models to ensure accurac...
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Delicate feature would become weaker or even disappear as going through deeper network layer, which results in jagged edges of objects in the depth estimation. To address this problem, we propose a multi-resolution at...
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The control of a nonlinear process raises various problems, both in terms of the control law design and the controller tuning. This paper presents a tuning procedure of a minimum variance control system based on the a...
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Facilitating dynamic bimanual handovers between humans and robots is a complex endeavor that requires integrating human pose estimation, motion prediction, and generating appropriate trajectories for receiving robots....
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The development of technology forces object detection algorithms to be a vital part in many aspects of technology, especially in artificial intelligence, autonomous vehicles, and computer vision. Intelligent Speed Ass...
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The advent of smart industry, propelled by the inte-gration of digital technologies and automation, has revolutionized manufacturing and industrial processes. robotics and artificial intelligence (AI) are at the foref...
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