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The aim of this paper is trying to propose an efficient method of inverse kinematics and motion generation for redundant humanoid robot arm based on the intrinsic principles of human arm motion. The intrinsic principle analysis takes into account both the skeletal kinematics and muscle strength properties. Firstly, this work analyzed the kinematic redundancy problem of a human arm. By analyzing the biological feature of a human arm, the kinematic redundancy boils down to the uncertainty of elbow position. Secondly, because the muscle’s kinematic and strength properties are critical for simulating biometric motion authentically, the muscle strength property was introduced as the criterion for configuration identification and motion generation. Three types of limb configuration, dog walking, gecko climbing, and human walking limb configuration were analyzed, and two geometrical configuration identification rules were deduced to generate biomimetic motion for humanoid robotic arms. By comparing the proposed method with other five IK methods, the proposed method significantly deduced the computing time. Finally, the configuration identification rules were used to generate motions for a 7-DoF humanoid robotic arm. The results showed that the biological rules can generate biomimetic, smooth arm motions for a redundant humanoid robotic arm.

In this research, a biological study is performed on the control of a quadruped walking robot. With a biomimetic observation of the gravity load receptor and stimulus-reaction mechanism of quadrupeds' locomotion and with the study of the stances on walking and energy efficiency, a new control method for a quadruped walking robot is derived. In particular, introduction of a new rhythmic pattern generator relieves the heavy computational burden because it does not need large computation on kinematics. The proposed controller, though it is simple, provides a useful framework for controlling a quadruped walking robot. In this paper, evaluation of the proposed method is done via a dynamic simulation. Then, it is validated by implementing in a quadruped walking robot, called AiDIN(Artificial Digitigrade for Natural Environment).

A low-cost, biologically inspired underwater walking robot (see Fig. 1) has been designed and built to covertly explore the seabed and to determine properties of submerged objects in obscure and inaccessible underwater locations. This paper focuses on a preliminary evaluation of an artificial active whisker to instrument this platform. Results demonstrate that both range and bearing to objects contacted by the whisker can be determined using simple data driven heuristics.