The manipulation of articulated objects plays an important role in real-world robot tasks, both in home and industrial environments. A lot of attention has been devoted to the development of ad hoc approaches and algorithms for generating the sequence of movements the robot has to perform in order to manipulate the object. Such approaches can hardly generalise on different settings, and are usually focused on 2D manipulations. In this paper we introduce a set of PDDL+ formulations for performing automated manipulation of articulated objects in a three-dimensional workspace by a dual-arm robot. Presented formulations differ in terms of how gravity is modelled, considering different trade-offs between modelling accuracy and planning performance, and between human-readability and parsability by planners. Our experimental analysis compares the formulations on a range of domain-independent planners, that aim at generating plans for allowing a dual-arm robot to manipulate articulated objects of different sizes. Validation is performed in simulation on a Baxter robot.

The manipulation of articulated objects is of primary importance in Robotics and can be considered as one of the most complex manipulation tasks. Traditionally, this problem has been tackled by developing ad hoc approaches, which lack flexibility and portability. In this paper, we present a framework based on answer set programming (ASP) for the automated manipulation of articulated objects in a robot control architecture. In particular, ASP is employed for representing the configuration of the articulated object for checking the consistency of such representation in the knowledge base and for generating the sequence of manipulation actions. The framework is exemplified and validated on the Baxter dual-arm manipulator in the first, simple scenario. Then, we extend such scenario to improve the overall setup accuracy and to introduce a few constraints in robot actions execution to enforce their feasibility. The extended scenario entails a high number of possible actions that can be fruitfully combined together. Therefore, we exploit macro actions from automated planning in order to provide more effective plans. We validate the overall framework in the extended scenario, thereby confirming the applicability of ASP also in more realistic Robotics settings and showing the usefulness of macro actions for the robot-based manipulation of articulated objects.

This paper addresses two intertwined needs for collaborative robots operating in shop-floor environments. The first is the ability to perform complex manipulation operations, such as those on articulated or even flexible objects, in a way robust to a high degree of variability in the actions possibly carried out by human operators during collaborative tasks. The second is encoding in such operations a basic knowledge about physical laws (e.g., gravity), and their effects on the models used by the robot to plan its actions, to generate more robust plans. We adopt the manipulation in three-dimensional space of articulated objects as an effective use case to ground both needs, and we use a variant of the Planning Domain Definition Language to integrate the planning process with a notion of gravity. Different complexity levels in modelling gravity are evaluated, which tradeoff model faithfulness and performance. A thorough validation of the framework is done in simulation using a dual-arm Baxter manipulator.

The manipulation of articulated objects is of primary importance in robotics, and is one of the most complex robotics tasks. Traditionally, this problem has been tackled by developing ad-hoc approaches, that lack of flexibility and portability. In this paper we present a framework based on Answer Set Programming (ASP) for the automated manipulation of articulated objects in a robot architecture. In particular, ASP is employed for representing the configuration of the articulated object, for checking the consistency of the knowledge base, as well as for generating the sequence of manipulation actions. The framework is validated both in simulation and on the Baxter dual-arm manipulator, showing the applicability of the ASP methodology in this complex application scenario.

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