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Two-legged locomotion is a much reseached topic in the robotics community since many decades. Nevertheless human walking and running is still unequaled. This paper introduces a biologically motivated approach of controlling bipeds that is based on recent results from neurological research on human walking. It features a hierarchical network of skills, motor patterns and reflexes that works locally and distributed and tries to exploit the natural dynamics of the system. The control concept is illustrated by the process of walking initiation.

Controlling biped robots in a human-like way is still in the air in robotics. Due to the existing of shortcomings of technical control methods, researchers began to try to find help from biomechanics, neuroscience, human movement analysis and other biological fields. This paper presents a biologically inspired method of controlling the locomotion of biped robots based on the neurological and biomechanical research of human walking. The control concept looks inside of the human motion control to generate an efficient, robust control approach for bipedal dynamic walking. The framework of the control approach consists of a hierarchical architecture of control network, motor patterns and reflexes that works locally and distributed to exploit the inherent dynamics of of the system. In this paper, the approach is validated on a simulated anthropomorphic biped with 21 DoFs. Several locomotion like standing, walking initiation and cyclic walking have been deeply studied. This paper will study the biomechanical aspect and motion analysis of termination of gait and its application in a biped robot. The corresponding reflexes and motor patterns will be also introduced in this paper.

For a legged robot that walks on rough terrain it is very important to avoid falling down while executing its mission. For this purpose, maintaining the six legged robot statically stable is considered an important issue and challenging task. This paper will shed light on the applied approach for detecting the direction of ground inclination, obstacle avoidance as well as the effect of amputation on statically stable up- and downhill walking based on evaluating the local current consumption and angular position of each leg’s joint. The body posture will be adjusted in relation to the direction of inclination. Our approach is based on an organic computing architecture and was tested on a low-cost version of the OSCAR robot.

Though over decades' development of bipedal robots, the terrains that bipedal robots can walk remains limited compared to what human can accomplish. To increase bipedal transversality on upslope terrain, this paper studies the biomechanical and biological aspects of human walking on inclined slopes with underlying the motor skills and reflexive systems. The control strategy can be divided into low and high gradient upslope walking. The strategy for the low gradient uphill walking is generated on the basis of an existing B4LC system. Furthermore, investigating the human walking on high gradient upslope terrain thoroughly unveils a new control strategy for bipedal walking on high gradient slope. Through validating the suggested method on a simulated biped upon different upslope terrains, the bipedal robot shows a naturally looking walking gait, achieving uphill walking up to 15° inclination which can compete with most advanced bipedal robots in the world.