A Survey of Robotic Harvesting Systems and Enabling Technologies

This paper presents a comprehensive review of ground agricultural robotic systems and applications with special focus on harvesting that span research and commercial products and results, as well as their enabling technologies. The majority of literature concerns the development of crop detection, field navigation via vision and their related challenges. Health monitoring, yield estimation, water status inspection, seed planting and weed removal are frequently encountered tasks. Regarding robotic harvesting, apples, strawberries, tomatoes and sweet peppers are mainly the crops considered in publications, research projects and commercial products. The reported harvesting agricultural robotic solutions, typically consist of a mobile platform, a single robotic arm/manipulator and various navigation/vision systems. This paper reviews reported development of specific functionalities and hardware, typically required by an operating agricultural robot harvester; they include (a) vision systems, (b) motion planning/navigation methodologies (for the robotic platform and/or arm), (c) Human-Robot-Interaction (HRI) strategies with 3D visualization, (d) system operation planning & grasping strategies and (e) robotic end-effector/gripper design. Clearly, automated agriculture and specifically autonomous harvesting via robotic systems is a research area that remains wide open, offering several challenges where new contributions can be made.

Modeling and analysis of a passively adaptive soft gripper with the bio-inspired compliant mechanism

Similar to the end effectors for traditional rigid robots, those for soft robots are essential as the interacting media between the robots and their environments. Inspired by the forelegs of climbing animals, a passively adaptive soft gripper (ASG), with six claws and a compliant mechanism, is developed for grasping objects and attaching to rough surfaces. The design method, grasp adaptability, form closure, and force equilibrium of the ASG are presented and analyzed in this paper. Due to the compliance at each claw root, the ASG possesses a high passive adaption to various objects. With sharp hooks, a form closure may be achieved easily when the ASG grasps rough objects with structured or unstructured shapes. The ASG grasping an object constitutes an under-actuated system, the solution to which is difficult to obtain. The Monte Carlo method is suggested to achieve effective solutions for such systems, and the in-hull rate is proposed to evaluate the difficulty of finding solution. Tests and experiments with the ASG grasping various objects have verified the adaptability and reliability of the ASG. The analytic and experimental results show that the novel ASG may be used as a universal gripper for soft manipulators and a prospective attaching device for biped climbing soft robots.

Grasp Configurations Optimization of Dexterous Robotic Hand Based on Haptic Exploration Information

Haptic exploration and grasp planning by dexterous robot hand are usually two independent research areas. In this paper, the determination of optimal grasp configurations after haptic exploration of unknown objects is discussed. The haptic exploration information is used to select initial grasp points and the corresponding robot configurations, which greatly improve the efficiency of grasp planning process. The feasible searching regions on the object are obtained under the constrains of manipulability and robot kinematics. Then, the optimization method based on KNN search is applied to find the optimal grasp positions in feasible searching regions. The selected optimal grasp points set can achieve high grasp quality under the constrains of robot kinematics and manipulability. The optimization method combines multiple grasp quality metrics, which is fast and feasible in optimal grasp points searching. Experiments validate the feasibility and effectivity of the proposed method.

Grasp quality measures: review and performance

The correct grasp of objects is a key aspect for the right fulfillment of a given task. Obtaining a good grasp requires algorithms to automatically determine proper contact points on the object as well as proper hand configurations, especially when dexterous manipulation is desired, and the quantification of a good grasp requires the definition of suitable grasp quality measures. This article reviews the quality measures proposed in the literature to evaluate grasp quality. The quality measures are classified into two groups according to the main aspect they evaluate: location of contact points on the object and hand configuration. The approaches that combine different measures from the two previous groups to obtain a global quality measure are also reviewed, as well as some measures related to human hand studies and grasp performance. Several examples are presented to illustrate and compare the performance of the reviewed measures.

New computational method for three-fingered force-closure test

This paper proposes an efficient implementation of a force-closure test for frictional three-finger grasps. The implementation is based on a condition that transforms force-closure testing into the problem of convex hull intersection in projective space. The proposed implementation further reduces the problem into the problem of computing whether a line segment intersects a convex hull of at most four points. Implementation results are presented along with a thorough performance analysis and comparison with several existing methods. The results are also verified with arbitrary precision floating point computation. This provides comparison of qualitative error resulting from floating point roundoff. The result shows that the proposed implementation outperforms other methods in terms of speed and precision.

Adaptive manipulation and slippage control of an object in a multi-robot cooperative system

Considering undesired slippage between manipulated object and finger tips of a multi-robot system, adaptive control synthesis of the object grasping and manipulation is addressed in this paper. Although many studies can be found in the literature dealing with grasp analysis and grasp synthesis, most assume no slippage between the finger tips and the object. Slippage can occur for many reasons such as disturbances, uncertainties in parameters, and dynamics of the system. In this paper, system dynamics is analyzed using a new presentation of friction and slippage dynamics. Then an adaptive control law is proposed for trajectory tracking and slippage control of the object as well as compensation for parameter uncertainties of the system, such as mass properties and coefficients of friction. Stability of the proposed adaptive controller is studied analytically and the performance of the system is studied numerically.

New advances in automatic selection of eligible surface elements for grasping and fixturing

Many object surfaces involve a number of pieces, expressed by different equations. Previous methods of optimal grasp planning can hardly cope with such cases. Ding et al. solve this problem by characterizing the object surface with convex facets and discrete points, then selecting the eligible ones for force-closure, and finally seeking the optimal contact positions on the selected elements. So far, however, no point contact with friction (PCwF) but only frictionless point contacts (FPC) can be used on the facets, while soft finger contacts (SFC) are excluded at all. In this paper, to the above two surface elements we add line segments. Moreover, the limitations on the contact types are completely removed. A general condition and a quantitative criterion of eligibility are presented, followed by a heuristic algorithm and an iterative algorithm for finding the better eligible elements. Three common examples show: the new advances make the formerly tough problems smoothly solvable.

Stochastic optimization-based approach for multifingered grasps synthesis

In this paper, we propose an approach for computing suboptimal grasps of polyhedral objects. Assuming n hard-finger contact with Coulomb friction model and based on central axes of the grasp wrench, we develop a new necessary and sufficient condition for n-finger grasps to achieve force-closure property. Accordingly, we reformulate the proposed force-closure test as a new linear programming problem, which we solve using an interior point method. Furthermore, we present an approach for finding appropriate stable grasps for a robotic hand on arbitrary objects. We use the simulated annealing technique for synthesizing suboptimal grasps of 3D objects. Through numerical simulations on arbitrary shaped objects, we show that the proposed approach is able to compute good grasps for multifingered hands within a reasonable computational time.