Gianni Vercelli

Shape analysis and hand preshaping for grasping

Observations of human grasping show two phases. During the reaching phase of grasping, the hand preshapes in order to prepare for the second phases which is shape-matching with the object. Planning of grasping with dextrous robot hands cannot be summarized to these two phases. It is necessary to split the grasping process into several phases (frequently overlapped), and to consider problems such as object recognition, planning accessibility, task planning, initial touch and grab phase, and stable grasp phase. These are consciously or unconsciously generated by a human being. A major issue is to integrate a part of these components in preshaping, and in particular in automatic planning accessibility and preshaping of objects to be grasped. The system is based on 2D analysis of slices extracted from an octree representation of objects.<<ETX>>

Achieving dextrous grasping by integrating planning and vision-based sensing

This article deals with the automation of dextrous grasping in a partly known environment using a stereo vision system and a multifingered hand mounted on a robot arm. Effective grasping requires a combination of sensing and planning capabilities: sensing to construct a well-adapted model of the situation and to guide the execution of the task, and planning to determine an appropriate grasping strategy and to generate safe, feasi ble manipulator motions. We propose an integrated approach that combines computer vision, path planning, and manipulator control in three complementary activities: the reconstruction of task-oriented models of the workspace, the determination of ap propriate grasping configurations from computed preshapes of the hand, and the automatic generation and execution of hand/arm motions using a hybrid geometric path planner and a hybrid control system. This article outlines the architec ture of our system, discusses the new models and techniques we have developed, and finishes with a brief description of work-in-progress on the implementation and some preliminary experimental results.

A Cognitive Hybrid Model for Autonomous Navigation

Action representation and planning is one among the most important research fields in which it has been experienced the failure of single paradigms in isolation to solve real, complex problems. The goal of this paper is to present a system for action representation and reasoning in complex, real-world, and real time scenarios, characterised by the integration of different representation paradigms: symbolic, diagrammatic, and procedural. In this sense the system is called “hybrid”. The paper focuses on the cognitive model and on the representation and reasoning system. A realistic navigation system for the guidance and control of autonomous mobile robots is used as an example to describe the potentiality of the system in solving real complex problems and it is currently being tested in an indoor environment.

Algorithms and architectures for acoustic localization based on microphone array in service robotics

This paper describes an experimental mobile robot with acoustic source localization capabilities for surveillance and transportation tasks in indoor environments. The location of a speaking operator is detected via a microphone array based algorithm; localization information are passed to a navigation module which sets up a navigation mission using knowledge of the environment map. The system has been developed using a distributed architecture with TCP/IP message passing. We describe the hardware and software architectures, as well as the algorithms. Experimental results describing the system performance in localization tasks are reported.

Grasping strategies for reconstructed unknown 3D objects

The authors describes an approach to the visuo-motor coordination of the grasping problem. A vision system is used to provide a spatial description of the scene. The volumetric information is reduced by merging the voxels into an octree representation. At the end of the reconstruction process, this kind of essential information can be used to choose the right pre-shaping and to coordinate the arm and the hand motion towards the pre-shaping position, in order to realize a stable grasp. Some preliminary results are shown.<<ETX>>

A reactive sensor-based system for solving navigation problems of an autonomous robot

In this paper we discuss the architecture a reactive agent that copes with autonomous robot navigation problems, with partial knowledge of the environment, and capable of accepting problems due to limit cycles or deadlocks. The agent is part of a general multilevel cognitive framework and we focus here on the model of the agent and the navigation problems it is well suited for, with particular attention to those ones which require a knowledge-based approach.

Multi-level navigation using active localization system

The traditional method for controlling the trajectories of an AGV in industrial environments is based on wire-guide systems. This paper describes a multi level architecture for mobile robots that integrates a high level mission planner, a real-time trajectory generator, and real-time motion control. The positioning accuracy is guaranteed by an active localization system that integrates in real-time the odometry measures giving position and orientation with high level resolution. This architecture allows the removal of the wire guidance system in AGV technology, and the introduction of an intelligent trajectory generation system at shop floor factory level.

Diagrammatic reasoning for planning and intelligent control

We describe a possible approach to planning starting from an emerging AI subfield. The models we propose are based on diagrammatic representations for reasoning about dynamic aspects of the world. Diagrammatic knowledge representation is an approach to knowledge representation in AI programs, that is suitable for problem solving and reasoning in spatial domains. Our claim is that diagrammatic representations could offer a way to combine AI and control system techniques for intelligent planning and control. The reason is that diagrammatic representations can share the high-level features of AI formalisms, such as explicit representations of objects, events, and situations, but with a finer-grained decomposition of actions and shapes. The dynamic aspects of our models are based on the metaphor of abstract potential fields (APF).

Pro-active service robots in a health care framework: vocal interaction using natural language and prosody

This paper describes a service robotics application in a health care environment. Human-robot interaction is based on the integration of low level skills like acoustic localization of noise/voice sources with high level competencies like continuous speech recognition and prosody based dialogue. A multirobotic system is presented; its coordination is performed by a central supervision device which manages the vocal interaction with a number of human operators. A microphone array placed on the top of the robots is used both for near talker location and for auto-localization through acoustic beacons. Preliminary experimental results are discussed.

Integration of active localization systems in vehicles control for real-time trajectory tracking

The introduction of intelligent mobile vehicles, both in industrial and civil applications, has a slow grow factor due to some fundamental limitations, an obvious one is the limited accuracy in trajectory generation and/or the heavy environmental restructuring required to allow affordable movement accuracy without a direct human supervision. On the other side, active localization systems offer good positioning accuracy, but suffer from timing problems which limit the use in dynamic applications where on-fly trajectory corrections of a pre-defined trajectory are required. In this paper we investigate the problem of integrating the use of active localization systems with traditional odometry in real-time trajectory generation, by the use of nontriangulation based algorithms. Different methods have been studied and tested, both in simulations and real environments. Preliminary experimental results are also presented in the last section of the paper.