As for the complex operational tasks in the unstructured environment with narrow workspace and numerous obstacles, the traditional robots cannot accomplish these mentioned complex operational tasks and meet the dexterity demands. The hyper-redundant bionic robots can complete complex tasks in the unstructured environments by simulating the motion characteristics of the elephant’s trunk and octopus tentacles. Compared with traditional robots, the hyper-redundant bionic robots can accomplish complex tasks because of their flexible structure. A hyper-redundant elephant’s trunk robot (HRETR) with an open structure is developed in this paper. The content includes mechanical structure design, kinematic analysis, virtual prototype simulation, control system design, and prototype building. This design is inspired by the flexible motion of an elephant’s trunk, which is expansible and is composed of six unit modules, namely, 3UPS-PS parallel in series. First, the mechanical design of the HRETR is completed according to the motion characteristics of an elephant’s trunk and based on the principle of mechanical bionic design. After that, the backbone mode method is used to establish the kinematic model of the robot. The simulation software SolidWorks and ADAMS are combined to analyze the kinematic characteristics when the trajectory of the end moving platform of the robot is assigned. With the help of ANSYS, the static stiffness of each component and the whole robot is analyzed. On this basis, the materials of the weak parts of the mechanical structure and the hardware are selected reasonably. Next, the extensible structures of software and hardware control system are constructed according to the modular and hierarchical design criteria. Finally, the prototype is built and its performance is tested. The proposed research provides a method for the design and development for the hyper-redundant bionic robot.
SUMMARY
In this paper, an online self-gain tuning method of a PD computed torque control (CTC) is used for a 3UPS-PS parallel robot. The CTC is applied to the 3UPS-PS parallel robot based on the robot dynamic model which is established via a virtual work principle. The control system of the robot comprises a nonlinear feed-forward loop and a PD control feedback loop. To implement real-time online self-gain tuning, an adjustment method based on the genetic algorithm (GA) is proposed. Compared with the traditional CTC, the simulation results indicate that the control algorithm proposed in this study can not only enhance the anti-interference ability of the system but also improve the trajectory tracking speed and the accuracy of the 3UPS-PS parallel robot.
This paper proposes an iterative algorithm to solve the inverse displacement for a hyper-redundant elephant’s trunk robot (HRETR). In this algorithm, each parallel module is regarded as a geometric line segment and point model. According to the forward approximation and inverse pose adjustment principles, the iteration process can be divided into forward and backward iteration. This iterative algorithm transforms the inverse displacement problem of the HRETR into the parallel module’s inverse displacement problem. Considering the mechanical joint constraints, multiple iterations are carried out to ensure that the robot satisfies the required position error. Simulation results show that the algorithm is effective in solving the inverse displacement problem of HRETR.
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