A 2D laser rangefinder scans dataset of standard EUR pallets

open5siopenIhab Mohamed, Alessio Capitanelli, Fulvio Mastrogiovanni, Stefano Rovetta, Renato ZaccariaMohamed, Ihab; Capitanelli, Alessio; Mastrogiovanni, Fulvio; Rovetta, Stefano; Zaccaria, RENATO UGO RAFFAEL

Manipulation of Articulated Objects using Dual-arm Robots via Answer Set Programming

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 a 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. Under consideration in Theory and Practice of Logic Programming (TPLP).Comment: Under consideration in Theory and Practice of Logic Programming (TPLP

On the manipulation of articulated objects in human-robot cooperation scenarios

Articulated and flexible objects constitute a challenge for robot manipulation tasks, but are present in different real-world settings, including home and industrial environments. Approaches to the manipulation of such objects employ ad hoc strategies to sequence and perform actions on them depending on their physical or geometrical features, and on a priori target object configurations, whereas principled strategies to sequence basic manipulation actions for these objects have not been fully explored in the literature. In this paper, we propose a novel action planning and execution framework for the manipulation of articulated objects, which (i) employs action planning to sequence a set of actions leading to a target articulated object configuration, and (ii) allows humans to collaboratively carry out the plan with the robot, also interrupting its execution if needed. The framework adopts a formally defined representation of articulated objects. A link exists between the way articulated objects are perceived by the robot, how they are formally represented in the action planning and execution framework, and the complexity of the planning process. Results related to planning performance, and examples with a Baxter dualarm manipulator operating on articulated objects with humans are shown

Long-Term Area Coverage and Radio Relay Positioning Using Swarms of UAVs

Unmanned Aerial Vehicles (UAVs) are becoming increasingly useful for tasks that require the acquisition of data over large areas. Online coverage algorithms obviously pose a greater challenge to ensure efficient operations with multiple UAVs compared to offline ones. Optimal relay positioning is a widely explored problem in the telecommunication field, where it is used to place antennas in a given area to provide robust wireless connection. The chapter presents the experiments used to assess the performance of the simultaneous coverage and relay-positioning algorithm and the related architecture. It proposes a novel approach to improve the performance of a UAVs swarm tasked to cover a given area in difficult contexts such as natural disasters. Future developments will deal with further increasing the robustness of the proposed architecture by exploring in detail the best strategies to adopt when multiple UAVs are busy with secondary tasks or to avoid the chain to be interrupted

Collaborative Robotic Manipulation:A Use Case of Articulated Objects in Three-dimensions with Gravity

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 trade-off model faithfulness and performance. A thorough validation of the framework is done in simulation using a dual-arm Baxter manipulator.Comment: This paper has been accepted for IEEE ICTAI 2020: https://ictai2020.org

KR&R approaches for robot manipulation tasks with articulated objects

In this paper we present two approaches for solving robot manipulation tasks with articulated objects by using knowledge representation and reasoning languages and tools. Such languages and tools are used both for representing initial and final configurations from an ontology description and for planning the robot (manipulation) actions. In the first approach, standard PDDL language and solvers are used to plan those actions, and DL solvers for ontology consistency checking. In the second (ongoing) approach, ASP is employed as a unifying framework for both ontology checking and planning