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202
Autonomous rover navigation on unknown terrains demonstrations in the space museum ”cite de l’espace” at toulouse automation
- In 7th International Symp. on Experimental Robotics
, 1997
"... Autonomous long range navigation in partially known planetary-like terrain is on open challenge for robotics. Nav-igating several hundreds of meters without any human interven-tion requires the robot to be able to build various representations of its environment, to plan and execute trajectories acc ..."
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Cited by 69 (3 self)
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Autonomous long range navigation in partially known planetary-like terrain is on open challenge for robotics. Nav-igating several hundreds of meters without any human interven-tion requires the robot to be able to build various representations of its environment, to plan and execute trajectories according to the kind of terrain traversed, to localize itself as it moves, and to schedule, start, control and interrupt these various activities. In this paper, we briefly describe some functionalities that are currently being integrated on board the Marsokhod model robot Lama at LAAS/CNRS. We then focus on the necessity to inte-grate various instances of the perception and decision function-alities, and on the difficulties raised by this integration. 1
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 humanaware motion planner must not only provide safe robot paths, but also synthesize good, socially acceptable and legible p ..."
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Cited by 56 (7 self)
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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 humanaware motion planner 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. Index Terms — HRI, Motion Planning, Social Interaction I.
Bayesian Robots Programming
- Research Report 1, Les Cahiers du Laboratoire Leibniz, Grenoble (FR
, 2000
"... We propose a new method to program robots based on Bayesian inference and learning. The capacities of this programming method are demonstrated through a succession of increasingly complex experiments. Starting from the learning of simple reactive behaviors, we present instances of behavior combinati ..."
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Cited by 42 (24 self)
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We propose a new method to program robots based on Bayesian inference and learning. The capacities of this programming method are demonstrated through a succession of increasingly complex experiments. Starting from the learning of simple reactive behaviors, we present instances of behavior combinations, sensor fusion, hierarchical behavior composition, situation recognition and temporal sequencing. This series of experiments comprises the steps in the incremental development of a complex robot program. The advantages and drawbacks of this approach are discussed along with these different experiments and summed up as a conclusion. These different robotics programs may be seen as an illustration of probabilistic programming applicable whenever one must deal with problems based on uncertain or incomplete knowledge. The scope of possible applications is obviously much broader than robotics.
Position estimation in outdoor environments using pixel tracking and stereovision
- In IEEE International Conference on Robotics and Automation
, 2000
"... This paper presents a method that estimates a robot displacements in outdoor unstructured terrain. It computes the displacements on the basis of associa-tions of 3D points sets produced by consecutive stere-ovision frames, the associations being determined by tracking pixels from one image frame to ..."
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Cited by 37 (12 self)
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This paper presents a method that estimates a robot displacements in outdoor unstructured terrain. It computes the displacements on the basis of associa-tions of 3D points sets produced by consecutive stere-ovision frames, the associations being determined by tracking pixels from one image frame to the other. The paper details the various steps of the algorithms, and presents first experimental results are presented: they show that the algorithm is able to estimate the 6 parameters of the robot position with a relative error smaller than about 5%, processing several hundreds of images over several tens of meters. 1
Constraint Solving in Uncertain and Dynamic Environments: A Survey
- Constraints
, 2005
"... Abstract. This article follows a tutorial, given by the authors on dynamic constraint solving at CP 2003 [87]. It aims at offering an overview of the main approaches and techniques that have been proposed in the domain of constraint satisfaction to deal with uncertain and dynamic environments. Keywo ..."
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Cited by 36 (3 self)
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Abstract. This article follows a tutorial, given by the authors on dynamic constraint solving at CP 2003 [87]. It aims at offering an overview of the main approaches and techniques that have been proposed in the domain of constraint satisfaction to deal with uncertain and dynamic environments. Keywords: constraint satisfaction problem, uncertainty, change, stability, robustness, flexibility
Ubiquitous networking robotics in urban settings
- In Proceedings of the IEEE/RSJ IROS Workshop on Network Robot Systems
"... Abstract- In this paper we will present the objectives of a ..."
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Cited by 32 (16 self)
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Abstract- In this paper we will present the objectives of a
Robot introspection through learned hidden Markov models
, 2006
"... In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behavioural models to provide a robot with an introspective capability. We assume that the behaviour of a robot in achieving a tas ..."
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Cited by 28 (6 self)
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In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behavioural models to provide a robot with an introspective capability. We assume that the behaviour of a robot in achieving a task can be modelled as a finite stochastic state transition system. Beginning with data recorded by a robot in the execution of a task, we use unsupervised learning techniques to estimate a hidden Markov model (HMM) that can be used both for predicting and explaining the behaviour of the robot in subsequent executions of the task. We demonstrate that it is feasible to automate the entire process of learning a high quality HMM from the data recorded by the robot during execution of its task. The learned HMM can be used both for monitoring and controlling the behaviour of the robot. The ultimate purpose of our work is to learn models for the full set of tasks associated with a given problem domain, and to integrate these models with a generative task planner. We want to show that these models can be used successfully in controlling the execution of a plan. However, this paper does not develop the planning and control aspects of our work, focussing instead on the learning methodology and the evaluation of a learned model. The essential property of the models we seek to construct is that the most probable trajectory through a model, given the observations made by the robot, accurately diagnoses, or explains, the behaviour that the robot actually performed when making these observations. In the work reported here we consider a navigation task. We explain
A Scheme for Coordinating Multi-robot Planning Activities and Plans Execution
- In Proceedings of the Thirteenth European Conference on Artificial Intelligence (ECAI-98
, 1998
"... . We present and discuss a generic scheme for multi-robot cooperation based on an incremental and distributed plan-merging process. Each robot, autonomously and incrementally builds and executes its own plans taking into account the multi-robot context. The robots are assumed to be able to collect t ..."
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Cited by 27 (1 self)
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. We present and discuss a generic scheme for multi-robot cooperation based on an incremental and distributed plan-merging process. Each robot, autonomously and incrementally builds and executes its own plans taking into account the multi-robot context. The robots are assumed to be able to collect the other robots plans and to coordinate their own plans with the other robots plans to produce "coordinated plans" that ensure their proper execution. We discuss the properties of this cooperative paradigm (coherence, detection of dead-lock situations, ...) , how it "fills the gap" between centralized and distributed planning and the class of applications for which it is well suited. We finally illustrate this scheme through an implemented system which allows a fleet of autonomous mobile robots to perform load transfer tasks in a route network environment with a very limited centralized activity and important gains in system flexibility and robustness to execution contingencies. 1 Introdu...
Propice-Plan: Toward a Unified Framework for Planning and Execution
"... In this paper, we investigate the links between planning and plans execution. We propose a new approach (Propice-Plan) whichintegrates both activities. It implements supervision and execution capabilities, combined with different planning techniques: -- plan synthesis to complement existing operatio ..."
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Cited by 27 (3 self)
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In this paper, we investigate the links between planning and plans execution. We propose a new approach (Propice-Plan) whichintegrates both activities. It implements supervision and execution capabilities, combined with different planning techniques: -- plan synthesis to complement existing operational plans; and -- anticipation planning to advise the execution for the best option to take when facing choices (by anticipating plans execution), and to forecast problems that may arise due to unforeseen situations. This approach relies on a common language to represent plans, actions, operational procedures and constraints. In particular, the description we propose makes transitions between planning activities and execution seamless. This work is used in two complex real-world problems: planning and control for autonomous mobile robots, and for the transition phases of a blast furnace.
Toward Developing Reusable Software Components for Robotic Applications
- in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS
, 2001
"... Abstract- We will present an overview of the CLARAty architecture which aims at developing reusable software components for robotic systems. These com-ponents are to support autonomy software which plans and schedules robot activities. The CLARAty architec-ture modifies the conventional three-level ..."
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Cited by 26 (7 self)
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Abstract- We will present an overview of the CLARAty architecture which aims at developing reusable software components for robotic systems. These com-ponents are to support autonomy software which plans and schedules robot activities. The CLARAty architec-ture modifies the conventional three-level robotic archi-tecture into a new two-layered design: the Functional Layer and the Decision Layer. The Functional Layer pro-vides a representation of the system components and an implementation of their basic functionalities. The Deci-sion Layer is the decision making engine that drives the Functional Layer. It globally reasons about the intended goals, system resources, and state of the system and its environment. The Functional Layer is composed of a set of interrelated object-oriented hierarchies consisting of active and passive objects that represent the different levels of system abstractions. In this paper, we present an overview of the design of the Functional Layer. The Functional Layer is decomposed into a set of reusable core components and a set of extended components that adapt the reusable set to different hardware implemen-tations. The reusable components: (a) provide interface definitions and implementations of basic functionality, (b) provide local executive capabilities, (c) manage local resources, and (d) support state and resource queries by the Decision Layer. I.
