Renato Zaccaria

Planning and obstacle avoidance in mobile robotics

The paper focuses on the navigation subsystem of a mobile robot which operates in human environments to carry out different tasks, such as transporting waste in hospitals or escorting people in exhibitions. The paper describes a hybrid approach (Roaming Trails), which integrates a priori knowledge of the environment with local perceptions in order to carry out the assigned tasks efficiently and safely: that is, by guaranteeing that the robot can never be trapped in deadlocks even when operating within a partially unknown dynamic environment. The article includes a discussion about the properties of the approach, as well as experimental results recorded during real-world experiments.

Path Following for Unicycle Robots With an Arbitrary Path Curvature

A new feedback control model is provided that allows a wheeled vehicle to follow a prescribed path. Differently from all other methods in the literature, the method that is proposed neither requires the computation of a projection of the robot position on the path, nor does it need to consider a moving virtual target to be tracked. Nevertheless, it guarantees asymptotic convergence to a generic 2-D curve which can be represented through its implicit equation in the form f(x,y)=0, and it puts no bounds on the initial position of the vehicle, provided that ∇f ≠ 0 .

Analysis of human behavior recognition algorithms based on acceleration data

The automatic assessment of the level of independence of a person, based on the recognition of a set of Activities of Daily Living, is among the most challenging research fields in Ambient Intelligence. The article proposes a framework for the recognition of motion primitives, relying on Gaussian Mixture Modeling and Gaussian Mixture Regression for the creation of activity models. A recognition procedure based on Dynamic Time Warping and Mahalanobis distance is found to: (i) ensure good classification results; (ii) exploit the properties of GMM and GMR modeling to allow for an easy run-time recognition; (iii) enhance the consistency of the recognition via the use of a classifier allowing unknown as an answer.

The artificial ecosystem: a distributed approach to service robotics

We propose a multiagent, distributed approach to autonomous mobile robotics which is an alternative to most existing systems in literature: robots are thought of as mobile units within an intelligent environment where they coexist and co-operate with fixed, intelligent devices that are assigned different roles: helping the robot to localize itself, controlling automated doors and elevators, detecting emergency situations, etc. To achieve this, intelligent sensors and actuators (i.e. physical agents) are distributed both onboard the robot and throughout the environment, and they are handled by Real-Time software agents which exchange information on a distributed message board. The paper outlines the benefits of the approach in terms of efficiency and Real-Time responsiveness.

GPS-based localization for a surveillance UGV in outdoor areas

The ANSER project (airport night surveillance expert robot) is described, exploiting a mobile robot for autonomous surveillance in civilian airports and similar wide outdoor areas. The paper focuses on the localization subsystem of the patrol robot: in contrast with most approaches in literature, we show how a positioning subsystem composed exclusively of a non-differential GPS unit (i.e., without inertial sensors) is enough to ensure accurate estimates of the robots position and orientation, under the assumption of nonholonomic kinematics.

Pre-emptive versus non-pre-emptive real time scheduling in intelligent mobile robotics

Autonomous and semi-autonomous mobile robots have to perform a multiplicity of concurrent activities in order to carry out useful tasks in unstructured human-populated environments. Even if it is commonly accepted that a successful accomplishment of assigned tasks requires some sort of real time capability to quickly react and adapt to environmental changes, it is not clear which operating system support is best suited for the scheduling and synchronizing of concurrent activities with different timing requirements. This paper discusses this problem, comparing two different real time scheduling policies for autonomous robot applications: pre-emptive rate monotonic and non pre-emptive Earliest Deadline First (EDF). Experimental results are presented and evaluated.

A programming environment for real-time control of distributed multiple robotic systems

In recent years there has been great interest in robot software control architectures. However, although many interesting solutions have been presented, most of the research problems tackled related to a single robot perception, navigation and action in everyday environments. Instead, most of the practical applications of mobile robotics for service tasks in civilian environments consist of systems composed of multiple robots communicating with each other, with external sensing and actuating devices, and with external supervising workstations. RoboCup offers a great opportunity to deal with this problem. In fact the software architecture of a robot soccer player must allow successful intra-robot integration of the different activities (visual perception, path planning, strategy planning, motion control, etc.) spanning many different types of representation (raw sensor data, images, symbolic plans, etc.) and it must also guarantee successful inter-robot integration by supporting communication and cooperation. This paper focuses on this problem, presenting ETHNOS-IV - a programming environment for the design of a real-time control system composed of different robots, devices and external supervising or control stations - which has been successfully used within the Italian ART robot team in the RoboCup-99 competition. ETHNOS provides support from three main point of views which will be addressed in detail: inter-robot and intra-robot communication, realtime task scheduling, and software engineering and code reuse. Experimental results illustrating the advantages of this approach will also be presented.

Petri net based process scheduling: A model of the control system of flexible manufacturing systems

In this paper, we propose a class of algorithms for the sub-optimal solution of a particular class of problems of process scheduling, particularly focusing on a case study in the area of flexible manufacturing systems (FMSs). The general class of problems we face in our approach is characterized as follows: there is a set of concurrent processes, each formed by a number of temporally related tasks (segments). Tasks are executable by alternate resource sets, different both in performance and costs. Processes and tasks are characterized by release times, due dates, and deadlines. Time constraints are also present in the availability of each resource in resource sets. It has been proven that such a problem does not admit an algorithm for an optimal solution in polynomial time. Our proposed algorithm finds a sub-optimal schedule according to a set of optimization criteria, based on task and process times (earliness, tardiness), and/or time independent costs of resources. Our approach to process scheduling is based on Timed Coloured Petri Nets. We describe the structure of the coordination and scheduling algorithms, concentrating on (i) the general-purpose component, and (ii) the application-dependent component. In particular, the paper focuses on the following issues: (i) theautomatic synthesis of Petri net models of the coordination subsystem, starting from the problem knowledge base; (ii) the dynamic behavior of the coordination subsystem, whose kernel is a High Level Petri net executor, a coordination process based on an original, general purpose algorithm; (iii) the structure of the real-time scheduling subsystem, based on particular heuristic sub-optimal multi-criteria algorithms. Furthermore, the paper defines the interaction mechanisms between the coordination and scheduling subsystems. Our approach clearly distinguishes the mechanism of the net execution from the decision support system. Two conceptually distinct levels, which correspond to two different, interacting implementation modules in the prototype CASE tool, have been defined: theexecutor and thescheduler levels. One of the outstanding differences between these levels is that the executor is conceived as a fast, efficient coordination process, without special-purpose problem-solving capabilities in case of conflicts. The scheduler, on the other hand, is the adaptive, distributed component, whose behavior may heavily depend on the problem class. If the scheduler fails, the executor is, in any case, able to proceed with a general-purpose conflict resolution strategy. Experimental results on the real-time performance of the kernel of the implemented system are finally shown in the paper. The approach described in this paper is at the basis of a joint project with industrial partners for the development of a CASE tool for the simulation of blast furnaces.

Distributing a robotic system on a network: the ETHNOS approach

Cognitive activity in intelligent robotic systems has often been modeled as a set of communicating intelligent distributed agents or modules. Some examples in this field are blackboard architectures, hybrid models or subsumption architectures. The rapid progress of communication technology offers the possibility of distributing computation not only on different processes but on a network of computers. This both results in greater available computational power and it allows the robot to merge with the environment it operates in. In suitable intelligent buildings a mobile robot may open doors, turn on/off lights or even avoid obstacles based not only on its sensors and actuators but on the interaction with other robotic entities. In addition the range of robot interactions is now only limited by the network and thus the robot can operate remotely on the environment. Similarly, users can issue commands to remote robots and receive feedback in real-time. In this paper we propose a global approach to distribut...

Context assessment strategies for Ubiquitous Robots

This paper presents an architecture for context-aware Ubiquitous Robotics applications, where mobile robots cooperate with intelligent environments to fulfill their tasks. Specifically, the work is focused on distributed knowledge representation issues and context assessment strategies, and introduces a technique for on-line context recognition in highly dynamic environments. Experimental validation, performed in a civillian hospital building, is described and discussed.