Искусственный интеллект (ИИ) и робототехника всегда были тесно связаны друг с другом. Одним из важных направлений ИИ до сих пор считается целенаправленное поведение роботов (создание интеллектуальных роботов, способных автономно совершать операции по достижению целей, поставлен-ных человеком). Сегодня мы наблюдаем узкую специализацию как в области технологий ИИ, так и в области робо-тотехники. Объясняется это тем, что изначально поставленные общие задачи оказались значительно более сложными, требующими создания совершенно иных моделей, методов и технологий, и прежде всего – технологий искусственного интеллекта. Достичь поставленных целей – создание интеллектуальных роботов, поодиночке невозможно, поскольку с одной стороны технологии ИИ должны управлять конкретным, а не «абстрактным» обору-дованием, имеющим свои особенности управления, а с другой стороны — робототехника не может обойтись без технологий ИИ. В работе был дан обзор состояния робототехники и интеллектуальных роботов на 2006 год. В данной работе предпринята попытка определить — какие изменения произошли за прошедшие четыре года в этой области и что нас ждет в ближайшем будущем.

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Determinants of locomotor training involve taskspecificity, repeata-bility, variability, intensity and self-initiative. KNEXO, a unilateral knee exoskeleton has been develo-ped to study the effects of compliant assistance during treadmill gait. Overall, walking within KNEXO, leads to asymmetric kinematics (Figure 1) and changes in naturally occurring muscle activity. Walking without KNEXO and with KNEXO in unassisted mode is difficult to compare as the device is unilateral and the pneumatic muscles give, although weight-compensated, a certain amount of inertia to the movement. Walking with KNEXO in high compliance resembles walking with KNEXO in unassisted mode. Overall, kinematic and EMG data show that the device has its shortcomings (unilateral, 1 DoF, 1 joint) when assisting healthy gait, yet it gives opportunities to study the effects of assistanceas-needed on gait biomechanics.

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Sometimes even identified — albeit incorrectly — with biomechanics, kinesiology is a field relying heavily on biomechanical methodology. Borellian Rennaisance approach, enhanced in the past with seminal contributions by scientists such as Marey, Braune, and Fischer, followed further by the work of the Berkeley Group, and later by a number of modern authors, has put classical me-chanics in the centre of a paradigm taken to understand, analyse and quantitatively assess human movement. As this framework sets both a geometrical and a dynamical definition of the spatial (three dimensional — 3D) movement of human body as a whole, an important further focus of the study may be directed to skeletal muscle itself, a basic actuator of movement and genuine biological system designed to produce mechanical force and cause movement. In this context, to monitor and evaluate human movement, we have a unique, second to none, method: electromyography (EMG); i.e. the recording of electrical activity of skeletal musculature. When studying kinesiological tasks, in particular, surface electromyography (sEMG) is the method’s variant of choice. To quote Hess (Hess, 1954, as cited in Waterland, 1968): „The course of a movement is nothing else but a projection to the outside of a pattern of excitation taking place at a corresponding setting in the central nervous system“. This thought reflects the importance of EMG signals as certain „windows“ into the action of the central nervous system during the performance of a motor task.

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This paper presents the results of the evaluation training performed in a group of chronic stroke patients with L-Exos device. The effects of training were assessed both by means of clinical evaluation in terms of Fugl-Meyer and Modified Ashworth assessment scales, and of functional evaluation, by means of Bimanual Activity Scale. Moreover at each session an automatic asses-sment of performance was made through the robot, and this was compared with the outcome of functional evaluation. Interestingly we found a significant improvement of both clinical and functional evaluation, and that the automatic assessment performed by the robot in terms of movement smoothness represents a strong predictor of transfer of functional ability to activity of every day life.

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The human history has been accompanied by accidental trauma, war, and congenital anomalies. Consequently, amputation and deformity have been dealt with, one way or another, throughout the ages. More than one million individuals in the United States today are living with limb amputations (Adams et al., 1999), in which there are approximately 100,000 patients with an upper limb amputation. The wars in Iraq and Afghanistan have added to this number. According to the survey results of the Second China National Sample Survey on Disables (SCNSSD 2006) led by the National Statistics Bureau in 2006, approximately 8% of physical disables, or 2.26 million people, live with limb amputations in China alone. Natural disasters and accidents have been making this number increase. The massive earthquakes that occurred in May 2008, Sichuan Province, China, recently increased about 20 thousand of new limb amputees. Expectations for control of upper limb prostheses have always been high because of the standard establi-shed by able-bodied dexterity.

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