Neural Task Programming: Learning to Generalize Across Hierarchical Tasks

In this work, we propose a novel robot learning framework called Neural Task Programming (NTP), which bridges the idea of few-shot learning from demonstration and neural program induction. NTP takes as input a task specification (e.g., video demonstration of a task) and recursively decomposes it into finer sub-task specifications. These specifications are fed to a hierarchical neural program, where bottom-level programs are callable subroutines that interact with the environment. We validate our method in three robot manipulation tasks. NTP achieves strong generalization across sequential tasks that exhibit hierarchal and compositional structures. The experimental results show that NTP learns to generalize well to- wards unseen tasks with increasing lengths, variable topologies, and changing objectives.Comment: ICRA 201

Acoustic Communication for Medical Nanorobots

Communication among microscopic robots (nanorobots) can coordinate their activities for biomedical tasks. The feasibility of in vivo ultrasonic communication is evaluated for micron-size robots broadcasting into various types of tissues. Frequencies between 10MHz and 300MHz give the best tradeoff between efficient acoustic generation and attenuation for communication over distances of about 100 microns. Based on these results, we find power available from ambient oxygen and glucose in the bloodstream can readily support communication rates of about 10,000 bits/second between micron-sized robots. We discuss techniques, such as directional acoustic beams, that can increase this rate. The acoustic pressure fields enabling this communication are unlikely to damage nearby tissue, and short bursts at considerably higher power could be of therapeutic use.Comment: added discussion of communication channel capacity in section

VI Workshop on Computational Data Analysis and Numerical Methods: Book of Abstracts

The VI Workshop on Computational Data Analysis and Numerical Methods (WCDANM) is going to be held on June 27-29, 2019, in the Department of Mathematics of the University of Beira Interior (UBI), Covilhã, Portugal and it is a unique opportunity to disseminate scientific research related to the areas of Mathematics in general, with particular relevance to the areas of Computational Data Analysis and Numerical Methods in theoretical and/or practical field, using new techniques, giving especial emphasis to applications in Medicine, Biology, Biotechnology, Engineering, Industry, Environmental Sciences, Finance, Insurance, Management and Administration. The meeting will provide a forum for discussion and debate of ideas with interest to the scientific community in general. With this meeting new scientific collaborations among colleagues, namely new collaborations in Masters and PhD projects are expected. The event is open to the entire scientific community (with or without communication/poster)

On the Encoding Capacity of Human Motor Adaptation

학위논문 (석사)-- 서울대학교 대학원 : 공과대학 기계공학부, 2019. 2. 박종우.가변 환경에 대한 인간 동역학의 적응은 인터널 모델의 개념으로 잘 설명된다. 인터널 모델은 일반적으로 운동 피질 뉴런에서 영감을 얻은 동적 원소들의 가중치 조합으로 매개 변수화된다. 동적 원소에 대한 다양한 표현이 존재하며 각 모델은 사람의 동역학 적응의 특성을 설명하는 데 성공했다. 그러나 인터널 모델이나 동적 원소를 통한 적응의 한계는 많이 연구되지 않았다. 더불어, 인터널 모델 학습을 연구할 때 신호 의존 노이즈를 고려하는 것이 중요함에도 불구하고, 그것에 대한 연구는 거의 진행되지 않았다. 이 논문에서 우리는 다음의 가설을 검증하고자 하였다: 인코딩 공간이 클수록 학습 효과가 더 좋다. 위치 오류 수준에서 우리는 외부 환경의 훈련 양과 신호 의존 노이즈이 어떻게 상호 작용을 하는지 외부 힘장 복잡성의 조절을 통해 조사했다. 특히 우리는 연속적인 원 운동에서 새로운 캐치 트라이얼을 개발하고 원 운동 중에 인간의 인터널 모델에 의해 추정 된 힘장을 정량적으로 측정했다. 위의 두 실험 결과는 제안 된 가설을 검증 할 수 있는 충분한 증거가 되었다. 실험 결과와 가설을 검증하기 위해 동적 원소의 조합을 기반으로 한 시뮬레이션 연구도 제안되었다.Adaptation of human dynamics to variable environments is well-explained with the concept of the internal model. The internal model is generally parametrized by a combination of motor primitives inspired from the motor cortex neurons. A variety of representations for motor primitives exists, and each model has succeeded in describing certain characteristics of dynamics adaptation. However, the limitations of adaptation explained via the internal model or motor primitives has not been thoroughly addressed in the literature. In particular, the fundamental question of how internal model learning behaves in the presence of signal-dependent noise has yet to be addressed. In this thesis, we try to verify the following hypothesis: the larger the encoding space, the better the learning. At the position error level, we investigate how the amount of training and signal-dependent noise interact to adjust the complexity of the force field. To experimentally validate our hypothesis, we perform a set of catch trials for continuous circular motions and quantitatively measure the force field estimated by a humans internal model during the motion. The above two experimental results provide evidence in support of our proposed hypothesis. A simulation study based on a combination of motor primitives is also proposed to verify the experimental results and hypotheses.Abstract (English) i List of Figures vi 1 Introduction 1 2 Human Motor Control Preliminaries 6 2.1 Basic features of human movement . . . . . . . . . . . . . . . . . . . 6 2.1.1 Smooth bell-shaped velocity profile . . . . . . . . . . . . . . 7 2.1.2 Fitts law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.3 Two-thirds power law . . . . . . . . . . . . . . . . . . . . . . 7 2.2 Computational model for human motor control . . . . . . . . . . . . 8 2.2.1 Optimization criterion on motor planning . . . . . . . . . . . 8 2.2.2 Signal-dependent noise : the minimum variance theory . . . 10 2.2.3 Optimal feedback control in motor coordination . . . . . . . 11 2.3 Human motor adaptation . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3.1 Internal model : state representation of motor learning . . . 13 2.3.2 Combination of motor primitives . . . . . . . . . . . . . . . . 15 iii 2.3.3 Gain encoding primitives for motor adaptation . . . . . . . . 16 2.3.4 Motor adaptation in circular movement . . . . . . . . . . . . 18 2.4 vBOT : robotic manipulandum for studying human motor control . 18 3 Rationale of the Study and Experimental Design 20 3.1 Making a movement versus maintaining a static posture . . . . . . 20 3.2 Experimental design and thesis statement . . . . . . . . . . . . . . . 24 4 Results and Discussion 26 4.1 Trade-off between encoding capacity and signal dependent noise . . 26 4.1.1 Expansion of logic: encoding capacity . . . . . . . . . . . . . 26 4.1.2 Experimental results for radial force . . . . . . . . . . . . . . 28 4.1.3 Experimental results for tangential force . . . . . . . . . . . 34 4.1.4 Discussion : radial force versus tangential force . . . . . . . 35 4.2 Influence of the mechanical factors during adaptation . . . . . . . . 37 4.2.1 Mechanical rebuttal for result analysis . . . . . . . . . . . . 37 4.2.2 Experimental results and discussion . . . . . . . . . . . . . . 37 4.3 Simulation results using motor primitives . . . . . . . . . . . . . . . 40 4.3.1 Problem definition . . . . . . . . . . . . . . . . . . . . . . . . 40 4.3.2 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . 41 5 Experimental Methods 43 5.1 General task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 5.2 External force-field . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 5.3 Main experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.3.1 Experiment 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.3.2 Experiment 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 iv 5.3.3 Experiment 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5.4 Catch trial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 5.4.1 Traditional catch trial for line movement . . . . . . . . . . . 50 5.4.2 New catch trial developed for continuous circular movement 51 6 Conclusion 53 Bibliography 54 Abstract (한글) 58Maste

Moving mass over a viscoelastic system: asymptotic behaviours and insights into nonlinear dynamics

Moving masses are of interest in many applications of structural dynamics, soliciting in the last decades a vast debate in the scientific literature. However, despite the attention devoted to the subject, to the best of the authors’ knowledge, there is a lack of analysis about the fate of a movable mass when it rolls or slips with friction on a structure. With the aim of elucidating the dynamics of the simplest paradigm of this system and to investigate its asymptotic response, we make reference to a two-degree-of-freedom model made of an elastically vibrating carriage surmounted by a spherical mass, facing the problem both theoretically and experimentally. In case of linear systems, the analytical solutions and the laboratory tests performed on ad hoc constructed prototypes highlighted a counterintuitive asymptotic dynamics, here called binary: in the absence of friction at the interface of the bodies’ system, the mass holds its initial position or, if nonzero damping acts, at the end of the motion it is in a position that exactly recovers the initial relative distance carriage–sphere. While the first result might be somewhat obvious, the second appears rather surprising. Such a binary behaviour is also confirmed for a Duffing-like system, equipped with cubic springs, while it can be lost when non-smooth friction phenomena occur, as well as in the case of elastic springs restraining the motion of the sphere. The obtained analytical results and the numerical findings, also confirmed by experimental evidences, contribute to the basic understanding of the role played by the damping parameters governing the systems’ dynamics with respect to its asymptotic behaviour and could pave the way for designing active or passive vibration controllers of interest in engineering

Controlled motion in an elastic world. Research project: Manipulation strategies for massive space payloads

The flexibility of the drives and structures of controlled motion systems are presented as an obstacle to be overcome in the design of high performance motion systems, particularly manipulator arms. The task and the measure of performance to be applied determine the technology appropriate to overcome this obstacle. Included in the technologies proposed are control algorithms (feedback and feed forward), passive damping enhancement, operational strategies, and structural design. Modeling of the distributed, nonlinear system is difficult, and alternative approaches are discussed. The author presents personal perspectives on the history, status, and future directions in this area