Weiwei Wan

This article develops model-based grasp planning algorithms. It focuses on industrial end-effectors like grippers and suction cups, and plans grasp configurations considering computer aided design (CAD) models of target objects. The developed algorithms can stably find many high-quality grasps, with satisfying precision and little dependency on the quality of CAD models. The undergoing core technique is superimposed segmentation, which preprocesses a mesh model by peeling it into superimposed fa

This paper presents a brief survey of robotic caging and its applications. Caging is a kind of grasping methods, which can be accomplished geometrically by position-controlled robotic agents, and has advantages over conventional manipulation which requires to fulfill mechanical conditions. Due to the advantages, caging was extensively studied and applied in robotics. This paper reviews the robotic literature related to caging ranging from its historical background, state-of-the-art developments,

In this paper, we propose a control algorithm to collectively transport an object using a group of relatively low-cost robots. We address this problem using the robust caging, which features reliable object closure with minimum number of robots, and requires no high-precision control capability on the individual robot. Given a 2-D convex object, the proposed method uses the quality of complete robustness to first optimize the number of robots in the initial formation, and then reorient and move

Purpose The purpose of this paper is to develop a planner for finding an optimal assembly sequence for robots to assemble objects. Each manipulated object in the optimal sequence is stable during assembly. They are easy to grasp and robust to motion uncertainty. Design/methodology/approach The input to the planner is the mesh models of the objects, the relative poses between the objects in the assembly and the final pose of the assembly. The output is an optimal assembly sequence, namely, in whi

This paper presents a manipulation planning algorithm for robots to reorient objects. It automatically finds a sequence of robot motion that manipulates and prepares an object for specific tasks. Examples of the preparatory manipulation planning problems include reorienting an electric drill to cut holes, reorienting workpieces for assembly, and reorienting cargo for packing, etc. The proposed algorithm could plan single- and dual-arm manipulation sequences to solve the problems. The mechanism u

This paper presents a novel approach to deal with uncertainty in grasping. The basic idea is to initiate a caging manipulation state and then shrink fingers into immobilization to perform a practical grasping. Thanks to flexibility from caging, this procedure is intrinsically safe and gains tolerance towards uncertainty. Besides, we demonstrate that the minimum caging is immobilization and consequently propose using three or four fingers to manipulate planar convex objects in a grasping-by-cagin

The goal of this paper is to develop a regrasp planning algorithm general enough to perform statistical analysis with thousands of experiments and arbitrary mesh models. We focus on pick-and-place regrasp which reorients an object from one placement to another by using a sequence of pick-ups and place-downs. We improve the pick-and-place regrasp approach developed in 1990s and analyze its performance in robotic assembly with different work surfaces in the workcell. Our algorithm will automatical

This paper presents an efficient algorithm to test whether a planar object can be caged by a formation of point agents (point fingertips or point mobile robots). The algorithm is based on a space mapping between the 2-D work space (W space) and the 3-D configuration space (C space) of the given agent formation. When performing caging test on a planar object, the algorithm looks up the space mapping to recover the C space of the given agent formation, labels the recovered C space, and counts the

“Grasping by caging” has been considered as a powerful tool to deal with uncertainty. In this paper, we continue to explore into “grasping by caging” and propose a new solution by using eigen-shapes and space mapping. For one thing, eigen-shapes fix dexterous hands into a series of finger formations and help to reduce dimensionality and computational complexity. For the other, space mapping builds a mapping between rasterized grids in 2-D Work space (W space) and rasterized voxels in 3-D Configu

We present a robotic system that can perform difficult reorientation tasks like flipping. The system uses a gripping hand and takes the advantages of external surfaces. It is composed by three components. In grasp planning, the system finds the grasps that fulfill force closure and resist high external wrenches. In placement planning, the system computes the stable placements of an object on the table surface and their associated grasps. In manipulation planning, the system builds a regrasp grap

The online system state initialization and simultaneous spatial-temporal calibration are critical for monocular Visual-Inertial Odometry (VIO) since these parameters are either not well provided or even unknown. Although impressive performance has been achieved, most of the existing methods are designed for filter-based VIOs. For the optimization-based VIOs, there is not much online spatial-temporal calibration method in the literature. In this paper, we propose an optimization-based online init

This paper presents an integrated assembly and motion planning system to recursively find the assembly sequence and motions to assemble two objects with the help of a horizontal surface as the supporting fixture. The system is implemented in both assembly level and motion level. In the assembly level, the system checks all combinations of the assembly sequences and gets a set of candidates. Then, for each candidate assembly sequence, the system incrementally builds regrasp graphs and performs re