Marilena Vendittelli

WMR control via dynamic feedback linearization: design, implementation, and experimental validation

The subject of the paper is the motion control problem of wheeled mobile robots (WMRs) in environments without obstacles. With reference to the popular unicycle kinematics, it is shown that dynamic feedback linearization is an efficient design tool leading to a solution simultaneously valid for both trajectory tracking and setpoint regulation problems. The implementation of this approach on the laboratory prototype SuperMARIO, a two-wheel differentially driven mobile robot, is described in detail. To assess the quality of the proposed controller, we compare its performance with that of several existing control techniques in a number of experiments. The obtained results provide useful guidelines for WMR control designers.

Fuzzy maps: A new tool for mobile robot perception and planning

An essential component of an autonomous mobile robot is the exteroceptive sensory system. Sensing capabilities should be integrated with a method for extracting a representation of the environment from uncertain sensor data and with an appropriate planning algorithm. In this article, fuzzy logic concepts are used to introduce a tool useful for robot perception as well as for planning collision-free motions. In particular, a map of the environment is defined as the fuzzy set of unsafe points, whose membership function quantifies the possibility for each point to belong to an obstacle. The computation of this set is based on a specific sensor model and makes use of intermediate sets generated from range measures and aggregated by means of fuzzy set operators. This general approach is applied to a robot with ultrasonic rangefinders. The resulting map building algorithm performs well, as confirmed by a comparison with stochastic methods. The planning problem on fuzzy maps can be solved by defining various path cost functions, corresponding to different strategies, and by searching the map for optimal paths. To this end, proper instances of the A* algorithm are devised. Experimental results for a Nomad 200™ robot moving in a real-world environment are presented.

Control of Wheeled Mobile Robots: An Experimental Overview

The subject of this chapter is the motion control problem of wheeled mobile robots (WMRs). With reference to the unicycle kinematics, we review and compare several control strategies for trajectory tracking and posture stabilization in an environment free of obstacles. Experiments are reported for SuperMARIO, a two-wheel differentially-driven mobile robot. From the comparison of the obtained results, guidelines are provided for WMR end-users.

The Sensor-based Random Graph Method for Cooperative Robot Exploration

We present a decentralized cooperative exploration strategy for a team of mobile robots equipped with range finders. A roadmap of the explored area, with the associate safe region, is built in the form of a sensor-based random graph (SRG). This is expanded by the robots by using a randomized local planner that automatically realizes a tradeoff between information gain and navigation cost. The nodes of the SRG represent view configurations that have been visited by at least one robot, and are connected by arcs that represent safe paths. These paths have been actually traveled by the robots or added to the SRG to improve its connectivity. Decentralized cooperation and coordination mechanisms are used so as to guarantee exploration efficiency and avoid conflicts. Simulations and experiments are presented to show the performance of the proposed technique.

The SRT method: randomized strategies for exploration

We present a method for sensor-based exploration of unknown environments by a mobile robot. The method is based on the randomized incremental generation of a data structure called sensor-based random tree (SRT), which represents a roadmap of the explored area with an associated safe region. Different exploration strategies may be obtained by instantiating the general method with different perception techniques. Two such techniques are discussed: the first, conservative and particularly suited to noisy sensors, results in an exploration strategy called SRT-Ball. The second perception technique is more confident, and the corresponding strategy is called SRT-Star. The two strategies are critically compared by simulations as well as by experiments on the MagellanPro robot.

A framework for the stabilization of general nonholonomic systems with an application to the plate-ball mechanism

We present a framework for the stabilization of nonholonomic systems that do not possess special properties such as flatness or exact nilpotentizability. Our approach makes use of two tools: an iterative control scheme and a nilpotent approximation of the system dynamics. The latter is used to compute an approximate steering control which, repeatedly applied to the system, guarantees asymptotic stability with exponential convergence to any desired set point, under appropriate conditions. For illustration, we apply the proposed strategy to design a stabilizing controller for the plate-ball manipulation system, a canonical example of nonflat nonholonomic mechanism. The theoretical performance and robustness of the controller are confirmed by simulations, both in the nominal case and in the presence of a perturbation on the ball radius.

On-line map building and navigation for autonomous mobile robots

The problem of sensor-based robot motion planning in unknown environments is addressed. The proposed solution approach prescribes the repeated sequence of two fundamental processes: perception and navigation. In the former, the robot collects data from its sensors, builds local maps and integrates them with the global maps so far reconstructed, using fuzzy logic operators. During the navigation process, a planner based on the A* algorithm proposes a path from the current position to the goal. The robot moves along this path until one of two termination conditions is verified namely (i) an unexpected obstructing obstacle is detected, or (ii) the robot is leaving the area in which reliable information has been gathered. Experimental results are presented for a Nomad 200 mobile robot.

Nonhomogeneous nilpotent approximations for nonholonomic systems with singularities

Nilpotent approximations are a useful tool for analyzing and controlling systems whose tangent linearization does not preserve controllability, such as nonholonomic mechanisms. However, conventional homogeneous approximations exhibit a drawback: in the neighborhood of singular points (where the system growth vector is not constant) the vector fields of the approximate dynamics do not vary continuously with the approximation point. The geometric counterpart of this situation is that the sub-Riemannian distance estimate provided by the classical Ball-Box Theorem is not uniform at singular points. With reference to a specific family of driftless systems, we show how to build a nonhomogeneous nilpotent approximation whose vector fields vary continuously around singular points. It is also proven that the privileged coordinates associated to such an approximation provide a uniform estimate of the distance.

Fuzzy logic and autonomous vehicles: experiments in ultrasonic vision

Abstract The opportunities offered by fuzzy logic to build maps for robot navigation are investigated. Characteristics of points of the space (occupied, free, uncertain, etc.) are easily expressed through set theoretical operations. Real-world experiments validate the approach. The experimental set-up is based on modified Polaroid ultrasonic sensors; however, the approach can be easily extended to incorporate other kinds of sensors.

Probabilistic motion planning for redundant robots along given end-effector paths

We consider the problem of planning collision-free motions for a redundant robot whose end-effector must travel along a given path. Although collision avoidance is one of the main reasons for introducing kinematic redundancy in manipulators, the planning methods so far proposed for this particular problem are neither efficient nor complete. In this paper, we introduce some algorithms that may be considered as an extension of probabilistic planning techniques to the problem at hand. All the algorithms are based on the same simple mechanism for generating random samples of the configuration space that are compatible with the end-effector path constraint. Experimental results illustrate the performance of the planners.