To address the issues of excessive parameters and a long training process, this study takes the TriMule-200 robot as an example and proposes a model-based and data-driven dynamic parameter identification approach. The approach designs a two-phase strategy of " source training phase & target training phase ": firstly, the rigid body dynamic model of the TriMule robot is established, and then 40 key dynamic parameters are selected by the Sobol global sensitivity analysis method. Subsequently, a neural network based on a Transformer encoder is constructed. In the source training phase, parameter sensitivity weights are introduced into the loss function, while in the target training phase, fine adjustment is made based on the error between the predicted torque of the model and the actual torque. Finally, a general identification software is developed based on this approach, which realizes the whole process modular integration from CAD model analysis, excitation trajectory design to fast parameter identification. The experiments on hybrid robot show that the predicted RMS error of the torque of the identified parameters is 3.16 ×10-2N·m , which is 17% lower than the calculated value based on CAD parameters, and the correlation coefficient is increased to 90.12%. In addition, the identification software can quickly adapt to similar hybrid robots with different sizes or varying loads, and online update of parameters can be achieved only by target training, significantly improving the accuracy of identification and engineering applicability.

Robot end-effector tracking of a specific spatial path to fulfill certain requirements is a topic of great interest. First, considering both dynamic constraints and kinematic constraints, the planned velocity has characteristics of bounded high-order derivatives to ensure smooth motion. Second, to meet high-efficiency requirements, the feedrate of the end-effector should be planned within the best possible time. Although some studies have shown that they obtained the time-optimal solution by considering the second-order constraints, this is still an open problem for third-order constraints. Therefore, this article proposes an approximate time-optimal feedrate (ATOF) planning algorithm that considers third-order constraints. This algorithm is primarily based on the bidirectional scanning method, which includes two steps. First, we calculate the second-order time-optimal velocity (TOV2) curve under the third-order maximum velocity curve. Then, considering TOV2, we propose an ATOF algorithm that includes single-direction speed planning and speed curve smoothing. It is more practical for not only considering the Coulomb viscous friction and torque rate but also avoiding difficult calculations at the singular point and solves discontinuous joint-acceleration under second-order constraints. Finally, we design two sets of experiments to verify the higher calculation efficiency and effectiveness of the proposed ATOF algorithm.

Drawing on screw theory and the virtual joint method, this paper presents a general and hierarchical approach for semianalytical stiffness modeling of parallel mechanisms. The stiffness model is built by two essential steps: 1) formulating the map between the stiffness matrices of platform and limbs using the duality of wrench and twist of the platform; and 2) formulating the map between stiffness matrices of a limb and a number of elastic elements in that limb using the duality of the wrench attributed to the limb and the twist of the endlink of that limb. By merging these two threads, the Cartesian stiffness matrix can be explicitly expressed in terms of the compliance matrices of joints and links. The proposed approach bridges the gap between two currently available approaches and is thereby very useful for evaluating stiffness over the entire workspace and investigating the influences of joint/link compliances on those of the platform in a quick and precise manner. A stiffness analysis for a 3-PRS parallel mechanism is presented as an example to illustrate the effectiveness of the proposed approach.

This paper presents a general and systematic approach to formulate the dimensionally homogeneous Jacobian, which is an important issue for the dexterity evaluation and dimensional synthesis off-degrees-of-freedom (DOF) (f≤ 6) parallel manipulators having mixed rotational and translational movement capabilities. By the utilization offindependent coordinates to describe the specified motion types of the platform, thef×fdimensionally homogeneous Jacobian is derived directly from the generalized Jacobian, provided that the manipulator has only one type of actuator. The condition number of the new Jacobian is then employed to evaluate the dexterity of two typical 3-DOF parallel manipulators as an illustration of the effectiveness of this approach.