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Proceedings of the 35th Florida Conference on Recent Advances in Robotics最新文献

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Humanoid Robot Motion Control for Ramps and Stairs 坡道和楼梯类人机器人运动控制
Tommy Truong, A. Weitzenfeld
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引用次数: 0
BLDC Actuators Revisited: A New Cost-Effective Design and Manufacturing for Robotic Applications 再访无刷直流驱动器:一种新的机器人应用成本效益设计和制造
Sean Bridges, Garhett Smith, Rene Preston, H. Sevil, Michael Reynolds
Brushless Direct Current (BLDC) actuators are recognized for their combined torque capabilities, precision control, and operational versatility, especially in regards to their smaller size. Actuators of this caliber are commonly implemented in high-performance industrial robotic arms, development in exoskeletal technologies, and quadrupedal robotic platforms. Professionally-developed brushless actuators available in the commercial sector deliver in their performance, however at a significant monetary expense. Our aim is to produce cost-efficient robotic actuators which are capable of replicating the design specifications and performance of commercial models. Our research focuses on the understanding and validation of fundamental principles of how brushless motors operate, and how the manipulation of respected variables can be combined to produce an optimized, robotic actuator design. The design and manufacturing process for each actuator prototype for this research revolves around a modular approach, where specific components can be repaired or replaced without compromising the structural integrity or robustness of the system. Each prototype utilizes a unique rotor and embedded planetary gearbox design as a mechanical means for increasing the potential torque output. Design constraints were set in place to properly analyze multi-variable combinations, which would ultimately maximize the electric torque density generated from induced electromagnetic forces. We believe that the results from our project can make cost-effective actuators available to the robotics community for advancing legged-locomotion robotic research.
无刷直流(BLDC)执行器以其组合扭矩能力,精确控制和操作通用性而闻名,特别是其较小的尺寸。这种口径的执行器通常用于高性能工业机械臂、外骨骼技术的开发和四足机器人平台。专业开发的无刷执行器在商业领域提供了他们的性能,但在很大的金钱费用。我们的目标是生产具有成本效益的机器人执行器,能够复制商业模型的设计规格和性能。我们的研究重点是理解和验证无刷电机如何运行的基本原理,以及如何将尊重变量的操作结合起来,以产生优化的机器人执行器设计。本研究的每个执行器原型的设计和制造过程都围绕模块化方法进行,可以在不影响系统结构完整性或稳健性的情况下修复或更换特定组件。每个原型都采用独特的转子和嵌入式行星齿轮箱设计作为增加潜在扭矩输出的机械手段。设计约束设置到位,以正确分析多变量组合,最终最大化感应电磁力产生的电转矩密度。我们相信,我们项目的结果可以为机器人社区提供具有成本效益的执行器,以推进有腿运动机器人的研究。
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引用次数: 0
Granular Material Extruder for Autonomous Asphalt Layer 自主沥青层用颗粒物料挤出机
Sebastian Story, Reinel Mota, Osmany Gonzalez, Kyle Reynolds, David Perez, Berry Lamy, I. Tansel
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引用次数: 0
Detection of Internal Voids of Additively Manufactured Parts with Structual Health Monitoring Methods 用结构健康监测方法检测增材制造零件的内部空洞
David Perez, Berry Lamy, Alireza Modir, Arnaud Casterman, I. Tansel
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引用次数: 0
Implementing Nonelinear Control of a Six Degree of Freedom Robotic Arm on a Raspberry Pi 3 在树莓派3上实现六自由度机械臂非线性控制
Hunter Smatla, Robert Shaw, Samuel Esse, Landen Rhodes
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引用次数: 0
Using Small UAS for STEM Education: Introducing Robotics and Mechatronics with Drones 在STEM教育中使用小型无人机:用无人机引入机器人和机电一体化
Christian Janke, Stefan Kleinke, Kimberly T. Luthi, Yuetong Lin
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引用次数: 0
POMDP Library Optimizing Over Exploration and Exploitation in Robotic Localization, Mapping, and Planning POMDP库优化在机器人定位,测绘和规划的探索和开发
J. Annan, Akram Alghanmi, M. Silaghi
Localization, mapping, and planning are critical in autonomous robots operating in uncertain environments and in continuous and discrete domains. High-quality probabilistic models for a complex robot depend heavily on details from its environment, involving multiple parameters. However, there is a lack of accurate probabilistic models for existing robots that can handle reasonably the challenges posed by real applications. For most robots, actions are highly non-deterministic. Furthermore, there is a lack of general software packages applicable to new scenarios. Specifically, we propose a POMDP library for optimal planning and localization given new available models, and dedicated to optimize over exploration and exploitation tradeoffs.
定位、映射和规划对于在不确定环境和连续和离散领域中运行的自主机器人至关重要。复杂机器人的高质量概率模型在很大程度上依赖于其环境的细节,涉及多个参数。然而,现有的机器人缺乏准确的概率模型来合理地处理实际应用所带来的挑战。对于大多数机器人来说,动作是高度不确定的。此外,缺乏适用于新场景的通用软件包。具体来说,我们提出了一个POMDP库,用于给定新的可用模型的最优规划和定位,并致力于优化过度勘探和开发权衡。
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引用次数: 0
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Proceedings of the 35th Florida Conference on Recent Advances in Robotics
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