Georges Giralt

Trajectory planning and motion control for mobile robots

This paper addresses two aspects of the navigation problem for a two d.o.f mobile robot (non holomic system): trajectory planning and motion control. Trajectory planning concerns the existence and the generation of a feasible collision-free trajectory, and motion control the actual execution of this trajectory.

Remote intervention, robot autonomy, and teleprogramming: generic concepts and real-world application cases

The authors consider the class of intervention robots that have to perform tasks in remote environments which may impose painful, harsh or utterly dangerous conditions to humans. They informally characterize this class of problems and briefly discuss several basic concepts which underlie the current approaches. The remote autonomous robot concept that they have developed fulfills the requirements deduced of these basic ideas. The authors illustrate the real world possibilities of the concept by describing the features of two application projects (AMR, VAP) that they believe to be significant and demonstrative. The last section is devoted to the description of a generic experiment carried on with ADAM, an all-terrain full size rover. It includes the system architecture implementation and some of the experimental results.

Task and path planning for mobile robots

Autonomous mobile robots represent today a perfect paradigm for third generation robots and possibly the clearest case study for machine intelligence. They imply multi-level environment perception and modelling, decisional autonomy ranging from general planning to specific task operating, autonomous mobility capacity, sophisticated high level man-machine interface, and efficient execution control systems.

Task Level Programming And Robot Autonomy

We consider the class of intervention mobile robots that huve to perform tasks in ill-known environments which are often remote or of difflicult or dangerous access. An outstanding example of this would be a Mars Rover designed to carry out planet exploration, scientific measurements and experiments, according lo the requeslis of Earth based scientists over a long period of time, e.g. one Martian year. The lack of structure in the environment of this class of intervention robots, as well as the nonrepetitive nature of the tasks, clearly require eficient task programming and constant adaptation to the environment by the robot. We contend that this class of problems demands a specific decisional architecture which couples “intelligence” at the programming level with “intelligence” at the level of the physical machine. This second requirement implies that the machine exhibits the attributes of an autonomous intelligent robot. In this paper we develop the concepts of a generic architecture aimed to achieve task control of a remote intervention robot. The robot is fully autonomous at task level. It receives tasks assignements that it transforms into sequences of actions using ats own interpretation and planning capacities, and executes these actions while being ,reactive to asynchronous events and environment conditions. We have developed the approach presented here in the context of several domain-oriented projects, and fully implemented a first version of the concepts in our newest mobile robot, HILARE II. The framework of the french Mars Rover project VAP is used as an illustration of some crucial aspects discussed in the paper.

Social Robots: Challenges for Machine Intelligence

Usually referred as Human Friendly Robotics and Human Centered Robotics, all those application cases emphasize the crucial aspect, well captured by Social Robots, of Human-Robot interaction issues where humans are most often non-expert users and by-standers. The very nature of this interaction brings to the forefront machine-intelligence central research issues of advanced Cognitive Robotics with key themes blending a large range of topics from embodiment and appearance to open-ended learning and decisional autonomy.