AbstractInspired by human nature, roboticists have conceived robots as tools meant to be flexible, capable of performing a wide variety of tasks. Learning from demonstration methods allow us to “teach” robots the way we would perform tasks, in a versatile and adaptive manner. Dynamic movement primitives (DMP) aims for learning complex behaviors in such a way, representing tasks as stable, well-understood dynamical systems. By modeling movements over the SE(3) group, modeled primitives can be generalized for any robotic manipulator capable of full end-effector 3D movement. In this article, we present a robot-agnostic formulation of discrete DMP based on the dual quaternion algebra, oriented to modeling throwing movements. We consider adapted initial and final poses and velocities, all computed from a projectile kinematic model and from the goal at which the projectile is aimed. Experimental demonstrations are carried out in both a simulated and a real environment. Results support the effectiveness of the improved method formulation.

AbstractAccurately analyzing the large deformation behaviors of compliant mechanisms has always been a significant challenge in the design process. The classical Euler–Bernoulli beam theory serves as the primary theoretical basis for the large deformation analysis of compliant mechanisms. However, neglecting shear effects may reduce the accuracy of modeling compliant mechanisms. Inspired by the beam constraint model, this study takes a step further to develop a Timoshenko beam constraint model (TBCM) for initially curved beams to capture intermediate-range deflections under beam-end loading conditions. On this basis, the chained Timoshenko beam constraint model (CTBCM) is proposed for large deformation analysis and kinetostatic modeling of compliant mechanisms. The accuracy and feasibility of the proposed TBCM and CTBCM have been validated through modeling and analysis of curved beam mechanisms. Results indicate that TBCM and CTBCM are more accurate compared to the Euler beam constraint model (EBCM) and the chained Euler beam constraint model (CEBCM). Additionally, CTBCM has been found to offer computational advantages, as it requires fewer discrete elements to achieve convergence.