Learning Algorithm for a Brachiating Robot

If charity begins at home, scholarship on the charitable deduction has stayed at home. In the vast legal literature, few authors have engaged the distinction between charitable contributions that are meant to be used within the United States and charitable contributions that are meant to be used abroad. Yet these two types of contributions are treated very differently in the Code and raise very different policy issues. As Americans\u27 giving patterns and the U.S. nonprofit sector grow increasingly international, the distinction will only become more salient. This Article offers the first exploration of how theories of the charitable deduction apply to internationally targeted donations. In so doing, the Article aims to contribute not only to a methodological shift in nonprofit tax scholarship (a strategic remapping), but also to a reappraisal of the deduction literature (an analytic remapping): just as existing theories of the deduction can inform our understanding of foreign charity, considerations of foreign charity can shed light back on the existing theories. I argue that the standard rationales are underdetermined and undertheorized, and propose a new, integrated approach to the charitable deduction. Internationally targeted donations emerge from the analysis holding a strong claim to deductibility – often a stronger claim than domestically targeted donations hold – on almost every relevant dimension, which calls into question current regulations that privilege domestic giving. Oversight and foreign policy concerns, however, complicate the ideal of geographic neutrality and illuminate the charitable deduction\u27s role as an instrument of statecraft. Admitting foreign charity into the debate over the deduction thus changes the debate\u27s terms; it gives deduction theory new urgency as well as new complexity

[[alternative]]Autonomous Dynamic Balance of Humanoid Robots(I)

計畫編號：NSC96-2218-E032-002研究期間：200708~200807研究經費：1,002,000[[abstract]]本計畫(即子計畫一)將著重於人型機器人自主動態平衡的研究，建立一 套能適應不同動作(例如，走路、上下樓梯、不平坦地面及跑步)及狀況(例 如，有無與境環互動、有無搭載重物)的機器人之動態平衡策略。相關的研 究主題包括如下：(一)機構設計，(二)伺服控制系統之設計，(三)設計動態 感知系統，(四)平坦地面走路、上下樓梯、不平坦地面走路及跑步之步態規 劃，(五)運動學及反運動學之推導，(六)以類神經網路近似反運動學，(七) 無支撐面(即跑步)動態方程式之推導，(八)單(及無)支撐面狀態之自我平 衡，(九)搭載重物與環境互動之自我平衡，及(十)具有可搭載重物及跑步能 力的人型機器人之開發。 第一年的研究主題為具有可搭載重物及跑步能力的人型機器人之機構 及伺服控制系統的設計，其中以加強伺服韌性及應用被動元件(例如，彈簧) 改善因跑步所引起地面衝擊力或搭載重物所須額外力矩；第二年的研究主 題為人型機器人之腳及手的運動學與反運動學之推導，並以類神經網路及 粒子群聚學習法則，近似具有限制的反運動學，以降低計算反運動學所須 的時間(或嵌入式系統的負荷)，亦完成單支撐面、搭載重物與環境互動狀態 之自我平衡；第三年的研究主題為無支撐面(即跑步)動態方程式之推導、 跑步步態之規劃、及自我動態平衡之策略。 配合子計畫二的雙眼可適應性視覺系統，執行子計畫四的視覺導引所要 求之動作；配合子計畫三的輸入輸出界面，設計PWM 驅動及DECODER 的PID 迴授控制之電路，並設計動態感知系統，以進行自主動態平衡；配合子計 畫四執行所下達的命令，完成所要求的智慧行為。[[sponsorship]]行政院國家科學委員

The development and walking control of biped robot

Master'sMASTER OF ENGINEERIN

Linear inverted pendulum model and swing leg dynamics in biped robot walking trajectory generation

Expectations of people and researchers from robotics have changed in the last four decades. Although robots are used to play their roles in the industrial environment, they are anticipated to meet social demands of people in daily life. Therefore, the interest in humanoid robotics has been increasing day by day. Their use for elderly care, human assistance, rescue, hospital attendance and many other purposes is suggested due to their adaptability and human like structure. Biped reference trajectory generation is a challenging task as well as control owing to the instability trend, non-linear robot dynamics and high number of degrees of freedom. Hence, the generated reference trajectories have to be followed with minimum control interference. Linear Inverted Pendulum Model (LIPM) is used to meet this demand which assumes the body as a falling point mass connected to the ground with a massless rod. The Zero Moment Point (ZMP) is a stability criterion for legged robots which provides a more powerful, stable reference generation. With the assistance of this methodology, advanced Linear Inverted Pendulum Models are implemented. This thesis aims to improve the applicability of the versatile and computationally effective LIPM based reference generation approach for the robots with heavy legs. It proposes a swing-leg gravity compensation technique based on a two-mass linear inverted pendulum model which is simulated on a discrete state space model. LIPM modeling is implemented by switching between one-mass and two-mass models during double support and single support phases, respectively. The joint trajectories are then obtained by inverse kinematics and PID controllers are employed independently at joint level for locomotion. The effectiveness of the generated reference trajectories is verified by simulation. The reference generation and control algorithm is tested with a 3-D full dynamic simulator on the model of a 12 DOF biped robot. Results indicate better performance of the one-mass-twomass switching LIPM over the one-mass LIPM

Steuerung eines zweibeinigen Schreitroboters mit einem elastischen Sensor-Aktor-System

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2012von Andriy Melnyko

Methods for Improving Motion Planning Using Experience

This thesis introduces new approaches to improve robotic motion planning by learning from past experiences especially suited for high-dimensional c-space with many invariant constraints. This experience-based motion planning (EBMP) paradigm reduces query resolution time, improves the quality of paths, and results in more predictable motions than typical probabilistic methods. Most previous approaches to motion planning have discarded past solution results and planned from scratch new solutions for every problem. A robot that is in operation for years will never get any better at its routine tasks. This thesis is novel in its focus on efficiently recalling previous motions the robot has performed and generalizing them to arbitrary new solutions even in the midst of changing obstacle environments. Several key difficulties present themselves in the reuse of previous experiences: efficient storage given memory constraints, quick recall for new queries, verification given changing environments, and adaptation/repair. These challenges are largely addressed by the use of sparse roadmaps that provide theoretical guarantees for asymptotic-near optimality, and lazy collision checking which allows iterative search through a large roadmap of motions. Improved sparse roadmap data structures for experience storage are presented that are optimized for the L1-norm metric and large c-spaces. The trade-offs of full preprocessing of an experience roadmap for invariant constraints is studied. These new approaches are applied to the high-dimensional problems of humanoid whole body manipulation, dual-arm shelf picking, and multi-modal underconstrained Cartesian planning. Experiments are implemented in the MoveIt! Motion Planning framework and takeaways from developing robot-agnostic motion planning software are presented. Experimental results show two orders of magnitude speedups for solving difficult motion planning problems.</p

Stabilizing Highly Dynamic Locomotion in Planar Bipedal Robots with Dimension Reducing Control.

In the field of robotic locomotion, the method of hybrid zero dynamics (HZD) proposed by Westervelt, Grizzle, and Koditschek provided a new solution to the canonical problem of stabilizing walking in planar bipeds. Original walking experiments on the French biped RABBIT were very successful, with gaits that were robust to external disturbances and to parameter mismatch. Initial running experiments on RABBIT were cut short before a stable gait could be achieved, but helped to identify performance limiting aspects of both the physical hardware of RABBIT and the method of hybrid zero dynamics. To improve upon RABBIT, a new robot called MABEL was designed and constructed in collaboration between the University of Michigan and Carnegie Mellon University. In light of experiments on RABBIT and in preparation for experiments on MABEL, this thesis provides a theoretical foundation that extends the method of hybrid zero dynamics to address walking in a class of robots with series compliance. Extensive new design tools address two main performance limiting aspects of previous HZD controllers: the dependence on non-Lipschitz finite time convergence and the lack of a constructive procedure for achieving impact invariance when outputs have relative degree greater than two. An analytically rigorous set of solutions - an arbitrarily smooth stabilizing controller and a constructive parameter update scheme - is derived using the method of Poincare sections. Additional contributions of this thesis include the development of sample-based virtual constraints, analysis of walking on a slope, and identification of dynamic singularities that can arise from poorly chosen virtual constraints.Ph.D.Electrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58477/1/morrisbj_1.pd