Searching force-closure optimal grasps of articulated 2D objects with n links

This paper proposes a method that finds a locally optimal grasp of an articulated 2D object with n links considering frictionless contacts. The surface of each link of the object is represented by a finite set of points, thus it may have any shape. The proposed approach finds, first, an initial force-closure grasp and from it starts an iterative search of a local optimum grasp. The quality measure considered in this work is the largest perturbation wrench that a grasp can resist with independence of the direction of the perturbation. The approach has been implemented and some illustrative examples are included in the article.Postprint (published version

Collision-free inverse kinematics of a 7 link cucumber picking robot

The paper presents results of research on inverse kinematics algorithms to be used in a functional model of a cucumber harvesting robot consisting of a redundant manipulator with one prismatic and six rotational joints (P6R). Within a first generic approach, the inverse kinematics problem was reformulated as a non-linear programming problem and solved with a generic algorithm. Solutions were easily obtained, but the considerable calculation time needed to solve the problem prevented on line implementation. To circumvent this problem, a second, less generic approach was developed consisting of a mixed numerical-analytic solution of the inverse kinematics problem exploiting the particular structure of the P6R manipulator. This approach facilitated rapid and robust calculation of the inverse kinematics of the cucumber harvester. During the early stages of the cucumber harvesting project, this inverse kinematics algorithm was used to off-line evaluate the ability of the robot to harvest cucumbers using 3D-information of a cucumber crop obtained in a real greenhouse. Thereafter, the algorithm was employed successfully in a functional model of the cucumber harvester to determine if cucumbers were hanging within the reachable workspace of the robot and to determine a collision-free harvest posture to be used for motion control of the manipulator during harvesting

Collision-free inverse kinematics of the redundant seven-link manipulator used in a cucumber picking robot

The paper presents results of research on an inverse kinematics algorithm that has been used in a functional model of a cucumber-harvesting robot consisting of a redundant P6R manipulator. Within a first generic approach, the inverse kinematics problem was reformulated as a non-linear programming problem and solved with a Genetic Algorithm (GA). Although solutions were easily obtained, the considerable calculation time needed to solve the problem prevented on-line implementation. To circumvent this problem, a second, less generic, approach was developed which consisted of a mixed numerical-analytic solution of the inverse kinematics problem exploiting the particular structure of the P6R manipulator. Using the latter approach, calculation time was considerably reduced. During the early stages of the cucumber-harvesting project, this inverse kinematics algorithm was used off-line to evaluate the ability of the robot to harvest cucumbers using 3D-information obtained from a cucumber crop in a real greenhouse. Thereafter, the algorithm was employed successfully in a functional model of the cucumber harvester to determine if cucumbers were hanging within the reachable workspace of the robot and to determine a collision-free harvest posture to be used for motion control of the manipulator during harvesting. The inverse kinematics algorithm is presented and demonstrated with some illustrative examples of cucumber harvesting, both off-line during the design phase as well as on-line during a field test

Fuzzy optimisation based symbolic grounding for service robots

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophySymbolic grounding is a bridge between task level planning and actual robot sensing and actuation. Uncertainties raised by unstructured environments make a bottleneck for integrating traditional artificial intelligence with service robotics. In this research, a fuzzy optimisation based symbolic grounding approach is presented. This approach can handle uncertainties and helps service robots to determine the most comfortable base region for grasping objects in a fetch and carry task. Novel techniques are applied to establish fuzzy objective function, to model fuzzy constraints and to perform fuzzy optimisation. The approach does not have the short comings of others’ work and the computation time is dramatically reduced in compare with other methods. The advantages of the proposed fuzzy optimisation based approach are evidenced by experiments that were undertaken in Care-O-bot 3 (COB 3) and Robot Operating System (ROS) platforms

A Minimalist Approach to Type-Agnostic Detection of Quadrics in Point Clouds

This paper proposes a segmentation-free, automatic and efficient procedure to detect general geometric quadric forms in point clouds, where clutter and occlusions are inevitable. Our everyday world is dominated by man-made objects which are designed using 3D primitives (such as planes, cones, spheres, cylinders, etc.). These objects are also omnipresent in industrial environments. This gives rise to the possibility of abstracting 3D scenes through primitives, thereby positions these geometric forms as an integral part of perception and high level 3D scene understanding. As opposed to state-of-the-art, where a tailored algorithm treats each primitive type separately, we propose to encapsulate all types in a single robust detection procedure. At the center of our approach lies a closed form 3D quadric fit, operating in both primal & dual spaces and requiring as low as 4 oriented-points. Around this fit, we design a novel, local null-space voting strategy to reduce the 4-point case to 3. Voting is coupled with the famous RANSAC and makes our algorithm orders of magnitude faster than its conventional counterparts. This is the first method capable of performing a generic cross-type multi-object primitive detection in difficult scenes. Results on synthetic and real datasets support the validity of our method.Comment: Accepted for publication at CVPR 201

Grasp Point Optimization and Leakage-Compliant Dimensioning of Energy-Efficient Vacuum-Based Gripping Systems

Vacuum-based handling, used in many applications and industries, offers great flexibility and fast handling processes. However, due to significant energy conversion losses from electrical energy to the useable suction flow, vacuum-based handling is highly energy-inefficient. In preliminary work, we showed that our grasp optimization method offers the potential to save at least 50% of energy by a targeted placement of individual suction cups on the part to be handled. By considering the leakage between gripper and object, this paper aims to extend the grasp optimization method by predicting the effective compressed air consumption depending on object surface roughness, gripper diameter and gripper count. Through balancing of the target pressure difference and the leakage tolerance in combination with the gripper count and gripper diameter, significant reductions of the compressed air, use and therefore the overall energy consumption, can be achieved. With knowledge about the gripper-specific leakage behavior, in the future it will be straightforward for system integrators to minimize the need for oversizing due to process-related uncertainties and therefore to provide application-specific and energy-optimized handling solutions to their customers