This paper explores the use of Robotics and decentralized Multi-Agent Reinforcement Learning (MARL) for side-by-side navigation in intelligent Wheelchairs (IW). Evolving from a previous work approach using traditional...
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ISBN:
(纸本)9798350352351;9798350352344
This paper explores the use of Robotics and decentralized Multi-Agent Reinforcement Learning (MARL) for side-by-side navigation in intelligent Wheelchairs (IW). Evolving from a previous work approach using traditional single-agent methodologies, it adopts a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to provide control input and enable a pair of IW to be deployed as decentralized computing agents in real-world environments, discarding the need to rely on communication between each other. In this study, the Flatland 2D simulator, in conjunction with the Robot Operating System (ROS), is used as a realistic environment to train and test the navigation algorithm. An overhaul of the reward function is introduced, which now provides individual rewards for each agent and revised reward incentives. Additionally, the logic for identifying side-by-side navigation was improved, to encourage dynamic alignment control. The preliminary results outline a promising research direction, with the IWs learning to navigate in various realistic hallways testing scenarios. The outcome also suggests that while the MADDPG approach holds potential over single-agent techniques for the decentralized IW robotics application, further investigation are needed for real-world deployment.
Cloud computing services and gig economy platforms vary in flexibility, efficiency, and scalability due to their pricing schemes. Cloud computing services provide flexibility and cost control via pay-as-you-go, subscr...
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For the cascaded planning and control modules implemented for robot navigation, the frequency gap between the planner and controller has received limited attention. In this study, we introduce a novel B-spline paramet...
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ISBN:
(纸本)9798350377712;9798350377705
For the cascaded planning and control modules implemented for robot navigation, the frequency gap between the planner and controller has received limited attention. In this study, we introduce a novel B-spline parameterized optimization-based planner (BSPOP) designed to address the frequency gap challenge with limited onboard computational power in robots. The proposed planner generates continuous-time control inputs for low-level controllers running at arbitrary frequencies to track. Furthermore, when considering the convex control action sets, BSPOP uses the convex hull property to automatically constrain the continuous-time control inputs within the convex set. Consequently, compared with the discrete-time optimization-based planners, BSPOP reduces the number of decision variables and inequality constraints, which improves computational efficiency as a byproduct. Simulation results demonstrate that our approach can achieve a comparable planning performance to the high-frequency baseline optimization-based planners while demanding less computational power. Both simulation and experiment results show that the proposed method performs better in planning compared with baseline planners in the same frequency.
With the rapid development of the economy and industrial production, industrial automation technology continues to improve, and the application of single-chip microcomputer automatic controlsystems in the industrial ...
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Class activation mapping (CAM) is a post-hoc explanation method for Convolutional neural networks (CNNs), aiming to visually explain the decision-making process of CNNs. CAM demonstrates superior categorical discrimin...
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Robot art presents an opportunity to both showcase and advance state-of-the-art robotics through the challenging task of creating art. Creating large-scale artworks in particular engages the public in a way that small...
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ISBN:
(纸本)9798350377712;9798350377705
Robot art presents an opportunity to both showcase and advance state-of-the-art robotics through the challenging task of creating art. Creating large-scale artworks in particular engages the public in a way that small-scale works cannot, and the distinct qualities of brush strokes contribute to an organic and human-like quality. Combining the large scale of murals with the strokes of the brush medium presents an especially impactful result, but also introduces unique challenges in maintaining precise, dextrous motion control of the brush across such a large workspace. In this work, we present the first robot to our knowledge that can paint architectural-scale murals with a brush. We create a hybrid robot consisting of a cable-driven parallel robot and 4 degree of freedom (DoF) serial manipulator to paint a 27m by 3.7m mural on windows spanning 2-stories of a building. We discuss our approach to achieving both the scale and accuracy required for brush-painting a mural through a combination of novel mechanical design elements, coordinated planning and control, and on-site calibration algorithms with experimental validations.
Soft pneumatic bending actuators (SPBAs) are commonly employed in soft robotics due to their unique characteristics, including safety, low weight, speed, and load capacity. However, the combination of pneumatics with ...
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ISBN:
(纸本)9798350377712;9798350377705
Soft pneumatic bending actuators (SPBAs) are commonly employed in soft robotics due to their unique characteristics, including safety, low weight, speed, and load capacity. However, the combination of pneumatics with soft materials causes SPBAs to exhibit nonlinearities and infinite degrees of freedom, complicating their dynamic modeling. In this work, we present how the dynamics of SPBAs can be adjusted to a fractional order model (FOM), showing an approach for their empirical identification. We also present a method for designing fractional order controllers (FOCs) for this type of actuators, based on the inversion of the empirical FOM. This modeling and control is applied to a modular SPBA made of a smart hydrogel, which endows the actuators with self-healing, self-adhesion, and self-sensing capabilities.
In recent years, with the emergence of new technologies such as smart manufacturing and smart factories, establishing effective and robust scheduling systems has become an important issue. The job shop scheduling prob...
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In this paper, we introduce the concept of using passive arm structures with intrinsic impedance for robot-robot and human-robot collaborative carrying with quadruped robots. The concept is meant for a leader-follower...
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ISBN:
(纸本)9798350377712;9798350377705
In this paper, we introduce the concept of using passive arm structures with intrinsic impedance for robot-robot and human-robot collaborative carrying with quadruped robots. The concept is meant for a leader-follower task and takes a minimalist approach that focuses on exploiting the robots' payload capabilities and reducing energy consumption, without compromising the robot locomotion capabilities. We introduce a preliminary arm mechanical design and describe how to use its joint displacements to guide the robot's motion. To control the robot's locomotion, we propose a decentralized Model Predictive controller that incorporates an approximation of the arm dynamics and the estimation of the external forces from the collaborative carrying. We validate the overall system experimentally by performing both robot-robot and human-robot collaborative carrying on a stair-like obstacle and on rough terrain.
This paper showcases the application of the Saturation in the Null Space (SNS) algorithm to establish task prioritization and coordination within a tele-operated minimally invasive robotic surgical setting. In our wor...
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ISBN:
(纸本)9798350377712;9798350377705
This paper showcases the application of the Saturation in the Null Space (SNS) algorithm to establish task prioritization and coordination within a tele-operated minimally invasive robotic surgical setting. In our work, SNS prioritizes achieving Remote Center of Motion (RCM) constraint, ensuring safe instrument manipulation, while respecting joint constraints for uninterrupted robot operation. This prioritization allows for accommodating the tracking of the surgeon's motion, within the capabilities defined by RCM and joint constraints. We investigate both the velocity and acceleration control variants of the SNS algorithm, incorporating bespoke adjustments to tailor the original algorithm to the intricate requirements of surgical applications. Through simulations and experiments, this work aims to demonstrate the effectiveness of SNS in enhancing the safety and controllability of tele-operated surgery, paving the way for its integration in various surgical procedures.
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