Latest Papers

ASME Journal of Mechanisms and Robotics

  • Theoretical Analysis of Workspace of a Hybrid Offset Joint
    on December 19, 2024 at 12:00 am

    AbstractOffset joints are widely used in robotics, and literature has demonstrated that axial offset joints can expand the workspace. However, the hybrid offset joint, which incorporates offsets in three orthogonal directions (x, y, and z axes), provides a more flexible and comprehensive range of motion compared to traditional axial offset joints. Therefore, a comprehensive understanding of the workspace of hybrid offset joints with three-directional offsets is essential. First, through a parameter model, the interference motion of hybrid offset joints is studied, considering three different directional offsets and obtaining analytical expressions. Next, based on coordinate transformations, the workspace of this joint is investigated, resulting in corresponding theoretical formulas. In addition, the influence of offset amounts in various directions on the joint’s workspace is examined. Finally, the application of hybrid offset joints in parallel manipulators (PMs) is introduced, highlighting their practical engineering value. Through comparative analysis, it is found that lateral offsets on the x- and y-axes adjust the maximum rotation angles, while the z-axis offset expands the rotational range of these joints. Moreover, by increasing the limit rotation angle of the passive joint in a specific direction, the application of hybrid offset joints in PMs can impact the workspace. These findings offer valuable insights for the design of hybrid offset joints and their applications in robotics.

  • A Novel Delta-Like Parallel Robot With Three Translations and Two Pitch Rotations for Peg-in-Hole Assembly
    on December 19, 2024 at 12:00 am

    AbstractThis paper presents a novel 5-degree-of-freedom (5-DOF) delta-like parallel robot named the double-pitch-delta robot, which can output three translations and two pitch rotations for peg-in-hole assembly. First, the kinematic mechanism of the new robot is designed based on the DOF requirements. Second, the closed-form kinematic model of the double-pitch-delta robot is established. Finally, the workspace of the double-pitch-delta robot is quantitatively analyzed, and a physical prototype of the new robot is developed to verify the effectiveness of the designed mechanism and the established models. Compared with the existing 5-DOF parallel robots with two pitch rotations, the double-pitch-delta robot has a simpler forward displacement model, larger workspace, and fewer singular loci. The double-pitch-delta robot can be also extended as a 6-DOF hybrid robot with the full-cycle tool-axis rotation to satisfy more complex operations. With these benefits, the new robot has a promising prospect in assembly applications.

Prediction of Human Reaching Pose Sequences in Human–Robot Collaboration

Abstract

In human–robot collaboration, robots and humans must work together in shared, overlapping, workspaces to accomplish tasks. If human and robot motion can be coordinated, then collisions between robot and human can seamlessly be avoided without requiring either of them to stop work. A key part of this coordination is anticipating humans’ future motion so robot motion can be adapted proactively. In this work, a generative neural network predicts a multi-step sequence of human poses for tabletop reaching motions. The multi-step sequence is mapped to a time-series based on a human speed versus motion distance model. The input to the network is the human’s reaching target relative to current pelvis location combined with current human pose. A dataset was generated of human motions to reach various positions on or above the table in front of the human starting from a wide variety of initial human poses. After training the network, experiments showed that the predicted sequences generated by this method matched the actual recordings of human motion within an L2 joint error of 7.6 cm and L2 link roll–pitch–yaw error of 0.301 rad on average. This method predicts motion for an entire reach motion without suffering from the exponential propagation of prediction error that limits the horizon of prior works.

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