A snake robot has to raise its head to acquire a wide visual space for planning complex tasks such as inspecting unknown environments, tracking a flying object and acting as a manipulator with its raising part. However, only a few researchers currently focus on analyzing the head-raising motion of snake robots. Thus, a predefined spiral curve method is proposed for the head-raising motion of such robots. First, the expression of the predefined spiral curve is designed. Second, with the curve and a line segments model of a snake robot, a shape-fitting algorithm is developed for constraining the robot’s macro shape. Third, the coordinate system of the line segments model of the robot is established. Then, phase-shifting and angle-solving algorithms are developed to obtain the angle sequences of roll, pitch, and yaw during the head-raising motion. Finally, the head-raising motion is simulated using the angle sequences to validate the feasibility of this method.
This paper proposes a kinematic obstacle avoidance algorithm for Space hyper-redundant manipulators, and its basic idea is to use a static and a dynamic curve to constrain the macroshape of the manipulators simultaneously. The static curve is constructed based on a traditional rapidly exploring random tree algorithm, and a backbone curve is utilized as the dynamic curve. For these two curves, two novel shape control methods are proposed to accomplish the shape constraining process. Finally, we verify the reliability and effectiveness of our algorithm through simulations.
At present, there is a problem of visual area switching in the existing SRL (supernumerary robotic limb) operation methods. In response to this problem, the authors’ previous work proposed a new SRL operation method called relatively independent operation, and proposed a corresponding software architecture. The purpose of this paper is to solve the theoretical problems and engineering realization problems of the human-SRL skeleton algorithm module in the software architecture. Therefore, modeling, data collection, data processing, and visualization of a human-SRL system are studied in this paper. Firstly, a human-SRL skeleton visualization simulation system is developed. The condition setting, the applications, and the core algorithm of the simulation system are introduced. The core algorithm mainly contains four types of important functions, namely skeleton model building functions, human-SRL data collection functions, human-SRL data processing functions, and skeleton visualization functions. Secondly, the implementation principles of these four functions are described: (1) For the skeleton model building functions, a human-SRL skeleton model is proposed which is an integration of a human skeleton model and an SRL skeleton model. The construction methods of these three skeleton models are described. (2) For the remaining functions, how to collect and process human data, SRL data, human-SRL data, and how to visualize a human-SRL skeleton are described. Finally, the visualization effect of the developed simulation system on human-SRL skeleton movement is verified by experiments, which proves the correctness of the functions in the simulation system.
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