Chuankai Liu

Vision-Based 3-D Grasping of 3-D Objects With a Simple 2-D Gripper

Object grasping or localization is an essential stage in automatic manufacturing processes. In general, stable grasping of 3-D objects is achieved by a multifinger hand. Different from the existing approaches, in this paper, we propose a novel vision-based method for grasping 3-D objects with a simple 2-D gripper. We describe the grasping strategy, the range of 3-D objects which can be grasped, and the region of grasping orientations which can guarantee successful actions. The proposed method facilitates the freedom of grasping orientation, which endows the strategy with a larger application range. Furthermore, we also explain the potential applications of the proposed method in grasping 3-D objects with other 2-D grippers. Although the proposed method uses a 2-D gripper and 2-D vision information, it can be regarded as a 3-D grasping approach due to the following facts. 1) The objects to be grasped are 3-D. The grasping process and the grasping orientations are analyzed and given in a 3-D space. 2) The contact points between the object and the gripper are not always in a 2-D plane. In the proposed method, the concept attractive region in configuration space, which was proposed in the previous work, is introduced to analyze the whole grasping process. Compared with other traditional methods, the proposed method directly gives the range of objects which can be grasped as well as the region of grasping orientations. By establishing the relationship between our method and traditional ones, it is proved that the bottom of the attractive region corresponds to a stable grasp.

Stable Sensorless Localization of 3-D Objects

In general, localization is a very important step in the manufacturing process, which can be considered as a prior process of assembly, machining, transportation, etc. Localization can be achieved with or without sensors. Compared with localization with sensors, localization without sensors can be more reliable, cheaper, and can have lower requirements on the environment. For example, localization without sensors can be achieved in a dark environment. However, it is more restrictive to the condition of the system. Localization of 2-D objects without sensors has been deeply investigated. Some theoretical results on 3-D-object localization without sensors have been given. On the other hand, some work has been carried out that tries to find methods to reduce uncertainties in the 3-D orientation of a polyhedron (i.e., the orientation of the polyhedron in a 3-D space). However, to the best of our knowledge, no practical and effective methods have been proposed, so far, to localize a polyhedron from any initial 3-D orientation to a unique 3-D orientation without sensors. This paper aims to find conditions and strategies for 3-D objects to be rotated from an unknown initial stable state to a unique stable state without sensors. The main contributions of this paper are given as follows: 1) It is discovered and proved that there are two classes of 3-D objects that can be rotated into a unique state from an arbitrary initial state without sensory feedback. 2) For these two classes of objects, the practical strategies are presented, and one example for each class is given to show the validity of the strategy. 3) Based on the above results, the robotic system and localization operations are illustrated, and some experimental results are given.

A vision-based 3D grasp planning approach with one single image

Many vision-based 3D grasping methods detect the stable grasping points based on several images. In their works, the full or partial 3D shape models are usually built for guiding the manipulations of the multi-DOF grippers. However, the uncertainties of detection and reconstruction of the contact points could lead to an unstable grasp. In this paper, the problem of vision-based 3D grasping from a single image of object is investigated, and the “attractive regions” proposed in our previous works [9] is utilized to analyze the 3D grasping process. (1) It is proven that a form closure grasp can be achieved if the state of 3D object is in the attractive region formed in the 3D grasping process. (2) Meanwhile, the initial contact regions, from which the 3D form-closure grasp can be achieved, are computed from the contour of the object. (3) A practical grasping system with four-finger gripper is designed, and a vision-based grasp planning approach is formulated. Finally, an experiment is conducted to show the efficiency of the proposed method.

Grasping Objects: The Relationship Between the Cage and the Form-Closure Grasp

In various industries, there is a need for low-cost, flexible robotic grasping systems that handle and classify different items, which usually involve low-cost grippers and reliable manipulations. One-degree-offreedom (1-DoF) two-pin or three-pin grippers are widely used in the automation of manufacturing processes because of their low cost and high reliability. However, some uncertainties introduced by the object and the gripper may affect the robustness of the grasp. The principle of caging enables us to deal with these uncertainties, and it is therefore important to study caging as a practical solution to improve the grasps of 1-DoF industrial grippers.

Introducing locally affine-invariance constraints into lunar surface image correspondence

This paper aims to solve the keypoint correspondence problem in lunar surface images, a typical correspondence task under point ambiguity. Point ambiguity may be caused by repetitive patterns, cluttered scenes, and outliers in the images, which makes the local descriptors less discriminative. In this paper we introduce locally affine-invariance constraints on graphs to tackle the keypoint correspondence problem under point ambiguity. The key idea is that each point can be represented with the affine combination of its neighbors. It is suitable for our problem because it is not only invariant to scale and rotational change, but also more resistant to outliers. Specifically, we introduce the locally affine-invariance constraints into the subgraph matching problem and the common subgraph matching problem. The locally affine-invariance constraint is not directly applicable on common subgraph matching due to its dependency on awareness of selected keypoints. This problem is approximately addressed by solving a series of reliable matching identification and rematching problems. In the experiments, we first apply the proposed method on standard graph matching datasets to evaluate its effectiveness on general correspondence problem under point ambiguity, and second validate the applicability on the lunar surface image dataset.

Pose-estimation and reorientation of pistons for robotic bin-picking

Purpose – Picking up pistons in arbitrary poses is an important step on car engine assembly line. The authors usually use vision system to estimate the pose of the pistons and then guide a stable grasp. However, a piston in some poses, e.g. the mouth of the piston faces forward, is hardly to be directly grasped by the gripper. Thus, we need to reorient the piston to achieve a desired pose, i.e. let its mouth face upward, for grasping. Design/methodology/approach – This paper aims to present a vision-based picking system that can grasp pistons in arbitrary poses. The whole picking process is divided into two stages. At localization stage, a hierarchical approach is proposed to estimate the piston’s pose from image which usually involves both heavy noise and edge distortions. At grasping stage, multi-step robotic manipulations are designed to enable the piston to follow a nominal trajectory to reach to the minimum of the distance between the piston’s center and the support plane. That is, under the design i...

A new practical strategy to localize a 3D object without sensors

Sensorless localization of 3D objects has been a significant research topic for many years. Researchers have focused on this problem from both theoretical and practical perspective where the goal is to reduce uncertainties in the orientation of a 3D object. However, to the best of our knowledge, no effective practical methods have been proposed so far to localize a polyhedron from any initial orientation to a unique orientation without sensors. In our previous work [1], two broad classes of 3D objects have been introduced, which can be localized from an arbitrary state to a unique state on a flat plane (the surface resting on the flat plane is established) without sensors. In this paper, a much broader class of polyhedra is introduced, which can be localized to a unique state without sensors. The main contributions of this paper are given as follows: • It is found that a polyhedron with an arbitrary initial state on the flat plane can be rotated to a fixed orientation (the orientation of the surface resting on the flat plane is fixed), provided that the polygon corresponding to each surface of the polyhedron can be oriented to a unique orientation in a 2D space. The method of rotating the polyhedron to a fixed orientation is given. • Base on the above result, both conditions and the strategy are given for a polyhedron to be localized to a unique state. • An example is given to show the validity of the strategy.

A New, Simple and Universal Four-Finger Gripper for 3D Objects Grasping

In manufacturing, it is common to handle objects with different geometries and weights. For example, there are more than ten types of objects required to assemble together in the automotive product line. The parallel-jaw gripper in wide use is inflexible and inefficient to meet the requirements. In this paper, a new, simple and flexible four-finger gripper, called CBF (Cross Bar Four-Finger) gripper, is designed to grasp various objects. The gripper with 8 degrees of freedom has compact architectures and can be easily built. It can perform both enveloping grasps and fingertip grasps. We present some properties of 3D objects that can be enveloping grasped. A sufficient condition is given for selecting the stable fingertip grasping points. Two strategies are proposed to select the contact points in two grasp modes respectively. Some examples are presented to validate our approach.