Self-organization of reflexive behavior from spontaneous motor activity.

In mammals, the development of reflexes is often regarded as an innate process. However, recent findings show that fetuses are endowed with favorable conditions for ontogenetic development. In this article, we hypothesize that the circuitry of at least some mammalian reflexes can be self-organized from the sensory and motor interactions brought forth in a musculoskeletal system. We focus mainly on three reflexes: the myotatic reflex, the reciprocal inhibition reflex, and the reverse myotatic reflex. To test our hypothesis, we conducted a set of experiments on a simulated musculoskeletal system using pairs of agonist and antagonist muscles. The reflex connectivity is obtained by producing spontaneous motor activity in each muscle and by correlating the resulting sensor and motor signals. Our results show that, under biologically plausible conditions, the reflex circuitry thus obtained is consistent with that identified in relation to the analogous mammalian reflexes. In addition, they show that the reflex connectivity obtained depends on the morphology of the musculoskeletal system as well as on the environment that it is embedded in.

Motor control optimization of compliant one-legged locomotion in rough terrain

While underactuated robotic systems are capable of energy efficient and rapid dynamic behavior, we still do not fully understand how body dynamics can be actively used for adaptive behavior in complex unstructured environment. In particular, we can expect that the robotic systems could achieve high maneuverability by flexibly storing and releasing energy through the motor control of the physical interaction between the body and the environment. This paper presents a minimalistic optimization strategy of motor control policy for underactuated legged robotic systems. Based on a reinforcement learning algorithm, we propose an optimization scheme, with which the robot can exploit passive elasticity for hopping forward while maintaining the stability of locomotion process in the environment with a series of large changes of ground surface. We show a case study of a simple one-legged robot which consists of a servomotor and a passive elastic joint. The dynamics and learning performance of the robot model are tested in simulation, and then transferred the results to the real-world robot. ©2007 IEEE.

Standing up with motor primitives

As observed in nature, complex locomotion can be generated based on an adequate combination of motor primitives. In this context, the paper focused on experiments which result in the development of a quality criterion for the design and analysis of motor primitives. First, the impact of different vocabularies on behavioural diversity, robustness of prelearned behaviours and learning process is elaborated. The experiments are performed with the quadruped robot MiniDog6M for which a running and standing up behaviour is implemented. Further, a reinforcement learning approach based on Q-learning is introduced which is used to select an adequate sequence of motor primitives. © 2006 Springer-Verlag Berlin Heidelberg.

Determination of sulfur-containing compounds in diesel oils by comprehensive two-dimensional gas chromatography with a sulfur chemiluminescence detector

This article reports an analytical method for separating, identifying and quantitating sulfur-containing compounds and their groups in diesel oils (170-400degreesC) using comprehensive two-dimensional gas chromatography coupled with a sulfur chemiluminescence detector. The identification of target compounds and their groups was based on standard substances, the group separation feature and the-effect of comprehensive two-dimensional gas chromatography. The quantitative analysis on major sulfur compounds and total sulfur was carried out based on the linear response of sulfur chemiluminescence detector and the internal standards method. The results of total sulfur determination in the samples were compared with those from ASTM D 4294 standard method, the R.S.D. percentage were <6.02%, correctness of this method can meet the industrial requirement. To the end, the method developed was used to investigate the sulfur-containing compounds in different diesel oils, the result shows that the distribution of sulfur-containing compounds in diesel oils from different process units are apparently different. The sulfur compounds in fluid catalytic cracking (FCC), residuum fluid catalytic cracking (RFCC) diesel oils mainly exist in the form of alkyl-substituted dibenzothiophenes that add up to about 40-50% of the total sulfur, while this number is only 6-8 and 20-28% in visbreaking (VB) and delayed-coking (DC) diesel oils, respectively. (C) 2003 Elsevier B.V. All rights reserved.

Roles of Knowledge in Motor Learning

The goal of this thesis is to apply the computational approach to motor learning, i.e., describe the constraints that enable performance improvement with experience and also the constraints that must be satisfied by a motor learning system, describe what is being computed in order to achieve learning, and why it is being computed. The particular tasks used to assess motor learning are loaded and unloaded free arm movement, and the thesis includes work on rigid body load estimation, arm model estimation, optimal filtering for model parameter estimation, and trajectory learning from practice. Learning algorithms have been developed and implemented in the context of robot arm control. The thesis demonstrates some of the roles of knowledge in learning. Powerful generalizations can be made on the basis of knowledge of system structure, as is demonstrated in the load and arm model estimation algorithms. Improving the performance of parameter estimation algorithms used in learning involves knowledge of the measurement noise characteristics, as is shown in the derivation of optimal filters. Using trajectory errors to correct commands requires knowledge of how command errors are transformed into performance errors, i.e., an accurate model of the dynamics of the controlled system, as is demonstrated in the trajectory learning work. The performance demonstrated by the algorithms developed in this thesis should be compared with algorithms that use less knowledge, such as table based schemes to learn arm dynamics, previous single trajectory learning algorithms, and much of traditional adaptive control.

Motor Control and Learning by the State Space Model

A model is presented that deals with problems of motor control, motor learning, and sensorimotor integration. The equations of motion for a limb are parameterized and used in conjunction with a quantized, multi-dimensional memory organized by state variables. Descriptions of desired trajectories are translated into motor commands which will replicate the specified motions. The initial specification of a movement is free of information regarding the mechanics of the effector system. Learning occurs without the use of error correction when practice data are collected and analyzed.

Considerações sobre biodiesel como biocombustível alternativo ao diesel.

Biodiesel é definido como o produto da reação de gordura animal ou vegetal com álcool (ou transesterificação). Tecnicamente podemos dizer que dos triglicerídeos presentes nessas matérias graxas (óleos vegetais ou animais), ésteres monoalquílicos (como os ésteres de etila e de metila) são produzidos pela reação com um álcool primário (etanol ou metanol) em meio preferencialmente alcalino. Esses ésteres também podem ser obtidos a partir de ácidos graxos livres, mas, nesse caso, a reação é de esterificação, e sua condução deve ser em meio preferencialmente ácido. As principais matérias-primas para a produção nacional do biodiesel são: soja, milho, girassol, amendoim, algodão, canola, mamona, babaçu, palma (dendê) e macaúba, entre outras oleaginosas existentes no país. O combustível também pode ser obtido a partir de óleos residuais e de gorduras animais. Além de ser uma tecnologia limpa, o emprego do biodiesel no óleo diesel de petróleo polui menos o meio ambiente, pode reduzir a dependência brasileira das importações de petróleo e trazer vantagens econômicas, pois sua produção e o cultivo das matérias-primas podem criar milhares de novos empregos, inclusive na agricultura familiar, principalmente nas regiões mais pobres do Brasil.

Growth of Motor Coordination in Early Robot Learning

M. H. Lee and Q. Meng, Growth of Motor Coordination in Early Robot Learning, IJCAI-05, 2005.

A Content-Neutral Approach for Sensory-Motor Learning in Developmental Robotics

M.H. Lee, Q. Meng and F. Chao, 'A Content-Neutral Approach for Sensory-Motor Learning in Developmental Robotics', EpiRob'06: Sixth International Conference on Epigenetic Robotics, Paris, 55-62, 2006.

Staged development of Robot Motor Coordination

M.H. Lee and Q. Meng, 'Staged development of Robot Motor Coordination', IEEE International Conference on Systems, Man and Cybernetics, (IEEE SMC 05), Hawaii, USA, v3, 2917-2922, 2005.

Psychologically Inspired Sensory-Motor Development in Early Robot Learning

Lee, M., Meng, Q. (2005). Psychologically Inspired Sensory-Motor Development in Early Robot Learning. International Journal of Advanced Robotic Systems, 325-334.

Psychologically Inspired Sensory-Motor Development in Early Robot Learning

M.H. Lee and Q. Meng, 'Psychologically Inspired Sensory-Motor Development in Early Robot Learning', in proceedings of Towards Autonomous Robotic Systems 2005 (TAROS-05), Nehmzow, U., Melhuish, C. and Witkowski, M. (Eds.), Imperial College London, 157-163, September 2005. See published version: http://hdl.handle.net/2160/485