Grasp Planning and Visual Servoing for an Outdoors Aerial Dual Manipulator

This paper describes a system for grasping known objects with unmanned aerial vehicles (UAVs) provided with dual manipulators using an RGB-D camera. Aerial manipulation remains a very challenging task. This paper covers three principal aspects for this task: object detection and pose estimation, grasp planning, and in-flight grasp execution. First, an artificial neural network (ANN) is used to obtain clues regarding the object’s position. Next, an alignment algorithm is used to obtain the object’s sixdimensional (6D) pose, which is filtered with an extended Kalman filter. A three-dimensional (3D) model of the object is then used to estimate an arranged list of good grasps for the aerial manipulator. The results from the detection algorithm—that is, the object’s pose—are used to update the trajectories of the arms toward the object. If the target poses are not reachable due to the UAV’s oscillations, the algorithm switches to the next feasible grasp. This paper introduces the overall methodology, and provides the experimental results of both simulation and real experiments for each module, in addition to a video showing the results.

Grasping Force Planning and Control for Tendon-driven Anthropomorphic Prosthetic Hands

A force planning and control method is proposed for a tendon-driven anthropomorphic prosthetic hand. It is necessary to consider grasping stability for the anthropomorphic prosthetic hand with multi degrees of freedom which aims to mimic human hands with dexterity and stability. The excellent grasping performance of the anthropomorphic prosthetic hand mainly depends on the accurate computation of the space position of finger tips and an appropriate grasping force planning strategy. After the dynamics model of the tendon-driven anthropomorphic prosthetic hand is built, the space positions of the finger tips are calculated in real time by solving the dynamic equations based on the Newton iteration algorithm with sufficient accuracy. Then, the balance of internal grasping force on the thumb is adopted instead of force closure of the grasped objects to plan the grasping forces of other fingers based on the method of the linear constraint gradient flow in real time. Finally, a fuzzy logic controller is used to control the grasping force of the prosthetic hand. The proposed force planning and control method is implemented on the tendon-driven anthropomorphic prosthetic hand and the experimental results dem- onstrate the feasibility and effectiveness of the proposed method.

A grasp planning algorithm under uneven contact point distribution scenario for space non-cooperative target capture

The contact point configuration should be carefully chosen to ensure a stable capture,especially for the non-cooperative target capture mission using multi-armed spacecraft.In this work scenario,the contact points on the base and on the arms are distributed on the opposite side of the target.Otherwise,large forces will be needed.To cope with this problem,an uneven-oriented distribution union criterion is proposed.The union criterion contains a virtual symmetrical criterion and a geometry criterion.The virtual symmetrical contact point criterion is derived from the proof of the force closure principle using computational geometry to ensure a stable grasp,and the geometry criterion is calculated by the volume of the minimum polyhedron formed by the contact points to get a wide-range distribution.To further accelerate the optimization rate and enhance the global search ability,a line array modeling method and a continuous-discrete global search algorithm are proposed.The line array modeling method reduces the workload of calculating the descent direction and the gradient available,while the continuous-discrete global search algorithm reducing the optimization dimension.Then a highly efficient grasping is achieved and the corresponding contact point is calculated.Finally,an exhaustive verification is conducted to numerically analyze the disturbance resistance ability,and simulation results demonstrate the effectiveness of the proposed algorithms.

Grasp evaluation and contact points planning for polyhedral objects using a ray-shooting algorithm

Grasp evaluation and planning are two fundamental issues in robotic grasping and dexterous manipulation. Most traditional methods for grasp quality evaluation suffer from non-uniformity of the wrench space and a dependence on the scale and choice of the reference frame. To overcome these weaknesses, we present a grasp evaluation method based on disturbance force rejection under the assumption that the normal component of each individual contact force is less than one. The evaluation criterion is solved using an enhanced ray-shooting algorithm in which the geometry of the grasp wrench space is read by the support mapping. This evaluation procedure is very fast due to the efficiency of the ray-shooting algorithm without linearization of the friction cones. Based on a necessary condition for grasp quality improvement, a heuristic searching algorithm for polyhedral object regrasp is also proposed. It starts from an initial force-closure unit grasp configuration and iteratively improves the grasp quality to find the locally optimum contact points. The efficiency and effectiveness of the proposed algorithms are illustrated by a number of numerical examples.