Rachid Alami

Bio: Rachid Alami is an academic researcher from University of Toulouse. The author has contributed to research in topics: Robot & Mobile robot. The author has an hindex of 50, co-authored 242 publications receiving 9450 citations. Previous affiliations of Rachid Alami include Hoffmann-La Roche & Laboratory for Analysis and Architecture of Systems.

An Architecture for Autonomy

Abstract: An autonomous robot offers a challenging and ideal field for the study of intelligent architectures. Autonomy within a rational be havior could be evaluated by the robot's effectiveness and robust ness in carrying out tasks in different and ill-known environments. It raises major requirements on the control architecture. Further more, a robot as a programmable machine brings up other archi tectural needs, such as the ease and quality of its specification and programming.This article describes an integrated architecture that allows a mobile robot to plan its tasks—taking into account temporal and domain constraints, to perform corresponding actions and to con trol their execution in real-time—while being reactive to possible events. The general architecture is composed of three levels: a de cision level, an execution level, and a functional level. The latter is composed of modules that embed the functions achieving sensor- data processing and effector control. The decision level is goal and event driven, a...

A Human Aware Mobile Robot Motion Planner

Abstract: Robot navigation in the presence of humans raises new issues for motion planning and control when the humans must be taken explicitly into account. We claim that a human aware motion planner (HAMP) must not only provide safe robot paths, but also synthesize good, socially acceptable and legible paths. This paper focuses on a motion planner that takes explicitly into account its human partners by reasoning about their accessibility, their vision field and their preferences in terms of relative human-robot placement and motions in realistic environments. This planner is part of a human-aware motion and manipulation planning and control system that we aim to develop in order to achieve motion and manipulation tasks in the presence or in synergy with humans.

How may I serve you?: a robot companion approaching a seated person in a helping context

Abstract: This paper presents the combined results of two studies that investigated how a robot should best approach and place itself relative to a seated human subject. Two live Human Robot Interaction (HRI) trials were performed involving a robot fetching an object that the human had requested, using different approach directions. Results of the trials indicated that most subjects disliked a frontal approach, except for a small minority of females, and most subjects preferred to be approached from either the left or right side, with a small overall preference for a right approach by the robot. Handedness and occupation were not related to these preferences. We discuss the results of the user studies in the context of developing a path planning system for a mobile robot.

M+: a scheme for multi-robot cooperation through negotiated task allocation and achievement

Abstract: We present and discuss a distributed scheme for multi-robot cooperation. It integrates mission planning and task refinement as well as cooperative mechanisms adapted from the contract net protocol framework. We discuss its role and how it can be integrated as a component of a complete robot control system. We also discuss how it handles distributed task allocation and achievement as well as cooperative reaction to contingencies. Finally, we illustrate its use through a simulated system, which allows a number of robots to perform load transfer tasks in a route network environment.

Planning Algorithms: Introductory Material

Abstract: Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

In Defense of the Triplet Loss for Person Re-Identification

Abstract: In the past few years, the field of computer vision has gone through a revolution fueled mainly by the advent of large datasets and the adoption of deep convolutional neural networks for end-to-end learning. The person re-identification subfield is no exception to this. Unfortunately, a prevailing belief in the community seems to be that the triplet loss is inferior to using surrogate losses (classification, verification) followed by a separate metric learning step. We show that, for models trained from scratch as well as pretrained ones, using a variant of the triplet loss to perform end-to-end deep metric learning outperforms most other published methods by a large margin.

Introduction to Autonomous Mobile Robots

Abstract: Mobile robots range from the Mars Pathfinder mission's teleoperated Sojourner to the cleaning robots in the Paris Metro. This text offers students and other interested readers an introduction to the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers the field comprises. The text focuses on mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks, including locomotion, sensing, localization, and motion planning. It synthesizes material from such fields as kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence, and probability theory. The book presents the techniques and technology that enable mobility in a series of interacting modules. Each chapter treats a different aspect of mobility, as the book moves from low-level to high-level details. It covers all aspects of mobile robotics, including software and hardware design considerations, related technologies, and algorithmic techniques.] This second edition has been revised and updated throughout, with 130 pages of new material on such topics as locomotion, perception, localization, and planning and navigation. Problem sets have been added at the end of each chapter. Bringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook or a working tool for beginning practitioners.