Maher Khatib

Reactive navigation in outdoor environments using potential fields

The paper presents an approach to reactive navigation in cross-country terrains. The approach relies on a particular probabilistic obstacle detection procedure, that describes the area perceived by a pair of stereo cameras as a set of polygonal cells. To generate the motion commands on the basis of this terrain description, we present some improvements and adaptations to the classical potential fields technique. Results on real stereo data illustrate our contribution throughout the paper, and simulated long range traverses are discussed.

Indoor navigation with uncertainty using sensor-based motions

This paper presents on operational framework to bridge the gap between planning with uncertainty and real-time sensor-based motion control. The environment being known, a planner produces a plan composed of free space and sensor-based motion commands. The representations of uncertainty and its evolution, environment landmarks, and actions generated at the planning level are discussed. Sensor-based actions and command definitions for a nonholonomic mobile robot based on a task-potential field approach are developed. These various elements are integrated in a system that actually generates the motions of the Hilare2 mobile robot.

A General Framework For Multi-Robot Cooperation and Its Implementation on a Set of Three Hilare Robots

We present a general concept for the control of a large fleet of autonomous mobile robots which has been developed, implemented and validated through various experiments.

Around the lab in 40 days [indoor robot navigation]

The authors previously (1998) argued that the LAAS architecture is one of the most suitable for mobile robot control. This statement may seem over-optimistic, not to say pretentious and unverifiable. After all, can we compare architectures? can we set up benchmarks? or can we measure how good an architecture is compared to another? An architecture defines organization principles, integration methods and supporting tools. Comparing those tools, methods and principles may sometime end up in sterile controversies. However, we think there are means to measure the overall quality (or interest) of an architecture. Development time is for example one relevant criterion. Basically, using a specific architecture, how long does it take to integrate a complete demonstration, including nontrivial decisional capabilities, from the low level functional modules up to the supervisory level? This may seem a rather weak measure of architecture quality; however, it encompasses properties such as genericity and adaptability, ease of design and programming, extensibility and robustness. In this paper we describe our recent experience in integrating a complete demonstration from scratch in 40 days using the LAAS architecture.

Sensor-based motion planning and control for the HILARE mobile robot

This paper presents the algorithms that have been developed and integrated onto the HILARE 2 mobile robot for achieving robust navigation, in presence of control and sensing errors, in an a priori known office-like environment. The mobile robot is equipped with a belt of 32 sonars and a laser range finder. Sonar data are used for the wall-following, move to contact and parallel actions. The laser is used for edge detection and matching during a wall-following. A VME rack supporting 6 CPU boards of the Motorola 680x0 family is mounted on the robot running under the VxWorks real-time system.

How to implement dynamic paths

Sensor-based dynamic path modification is one of powerful issues to combine planning and reactive control. This paper treats problems related to flexible trajectories implementation and presents solutions to connect functional levels from the planning to the execution. A general dynamic path structure is proposed and discussed including execution needs and constraints. Implementation algorithms are then developed and presented for general metrics and execution contexts. Finally, solutions for car-like mobile robots are encapsulated in a complete system joining these different levels and mange there functional coherence.

Object Recognition for a Grasping Task by a Mobile Manipulator

This paper presents the work currently done at LAAS/CNRS about scene interpretation required for manipulation tasks by a mobile arm. This task is composed of two steps : the approach of the mobile platform along the manipulation site and the grasping itself. The paper focuses on the object recognition and localization : the approach step is performed by a simple laser-based navigation procedure. For the grasping step, we use a CAD model of the object and discuss of the problems linked with such a representation : visibility informations must be added so that recognition and grasping strategies could be selected in a formal way. For the recognition, first matchings concerning discriminant patterns allow to generate a first prediction about the object situation; an optimal verification viewpoint can be computed. From this new camera position, we search for maximal sets of matched image features and model primitives; the best recognition hypothesis is determined by the best score. If no prediction can be determined, the system may switch to other discriminant patterns or move the camera respectfull to the arm and robot constraints.

Interleaving Motion Planning And Execution For Mobile Robots

Motion planning and control for a mobile robot are often considered as two different and sequential processes. However, in a real environment where the robot is subject to perturbations induced by other moving agents or incomplete and uncertain models, it appears necessary to bridge the gap between planning and execution. The presented approach consists in considering the planned path as an indication by an execution system that will have some freedom in the actual motion control. The questions discussed in this paper are then: What is a planned path? How does the execution system modify it on-line? How are the kinematic features of the robot taken into account? The approach relies on an extensive use of potential fields for defining sensor-based motions, as well as for dynamic path modification. Experimental results show the effectiveness of the algorithms.