Stéphane BazeilleUniversité de Haute-Alsace | UHA · IRIMAS
Stéphane Bazeille
Ph.D. in perception for underwater robots
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44
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Introduction
I am a lecturer at Université de Haute Alsace (France). I am interested in the problem of environment perception (from object recognition to mapping) for mobile and underwater robots. From 2005-2008 and 2015 to 2017 i was researcher in the field of underwater robots (in Brest and Nantes). From 2008 to 2015, I developed SLAM algorithms and designed the perception systems for terrestrials robots (in Paris and Genoa). I received my PhD in 2008 from Western Brittany University.
https://sites.google.com/site/bazeilst/
Skills and Expertise
Publications
Publications (44)
In recent years, autonomous vehicles have become an axis of academic and industrial research. Localizing these vehicles without a GPS signal represents a challenge for researchers, because the other sensors are usually less accurate, less fast and require more computation. Among localization methods, dead reckoning ones do not need prior knowledge...
The navigation and guidance of autonomous vehicles require precise and accurate localization. However, in some situations the use of dead reckoning localization is unavoidable, despite the fact that it introduces an accumulation of errors known as drift. This paper focuses on a comparison in simulation between three different localization drift mod...
This work presents how deflectometry can be coupled with a light-field camera to better characterize and quantify the depth of anomalies on specular surfaces. In our previous work,1 we proposed a new scanning scheme for the detection and 3D reconstruction of defects on reflective objects. However, the quality of the reconstruction was strongly depe...
In the 50s, biologists discovered that some electric fish is capable of discriminating the pose as well as the electric and geometric properties of surrounding objects by navigating and measuring the distortions of a self-generated electric field. In this article, we address the challenging issue of ellipsoidal objects pose and size estimation for...
In computer vision, the epipolar geometry embeds the geometrical relationship between two views of a scene. This geometry is degenerated for planar scenes as they do not provide enough constraints to estimate it without ambiguity. Nearly planar scenes can provide the necessary constraints to resolve the ambiguity. But classic estimators such as the...
In the past few years, a new type of camera has been emerging on the market: a digital camera capable of capturing both the intensity of the light emanating from a scene and the direction of the light rays. This camera technology called a light-field camera uses an array of lenses placed in front of a single image sensor, or simply, an array of cam...
This article presents different use of the electric sense perception in the context of underwater robot navigation. To illustrate the developed navigation behaviours we will introduce a recently launched european project named subCULTron and will show some simulation and experimentation results. The project subCULTron aims at achieving long-term co...
This paper presents the research done in the field of robotic cultural evolution in challenging real world environments. We hereby present these efforts, as part of project subCULTron, where we will create an artificial society of three cooperating sub-cultures of robotic agents operating in a challenging real-world habitat. We introduce the novel...
Recently, biologists have shown that the weakly electric fish are able to estimate the electric nature, the localization and the 3D geometric properties of an object using active electric sense. Incredibly, the Gnathonemus petersii performs this task in the dark only by moving towards and around the object, its vision is not required. In this paper...
In this article we address the issue of shape estimation using electric sense inspired by the active electric fish. These fish can perceive their environment by measuring the perturbations in a self-generated electric field caused by nearby objects. The approach proceeded in three stages. Firstly, the object was detected and its electric properties...
Reliable state estimation is crucial for stable planning and control of legged locomotion. A fundamental component of a state estimator in legged platforms is Leg Odometry, which only requires information about kinematics and contacts. Many legged robots use dedicated sensors on each foot to detect ground contacts. However, this choice is impractic...
Legged robots have the potential to navigate in more challenging terrains than wheeled robots. Unfortunately, their control is more demanding, because they have to deal with the common tasks of mapping and path planning as well as more specific issues of legged locomotion, like balancing and foothold planning. In this paper, we present the integrat...
Agile robot locomotion on rough terrain is highly dependent on the ability to perceive the environment. In this paper, we show how the interaction between a reactive control framework and an online mapping system can significantly improve the trotting performance on irregular terrain. In particular, this new locomotion controller increases the stab...
We present a real-time SLAM system that combines an improved version of the Iterative Closest Point (ICP) and inertial dead reckoning to localize our dynamic quadrupedal machine in a local map. Despite the strong and fast motions induced by our 80 kg hydraulic legged robot, the SLAM system is robust enough to keep the position error below 5% within...
We address the problems of localization, mapping and guidance for robots with limited computational resources by combining vision with the metrical information given by the robot odometry.
We propose in this paper a novel light and robust topo-metric SLAM framework using appearance based visual loop-closure detection enhanced with the odometry.
T...
Legged robots are expected to have superior mobility on rough terrain than wheeled robots. The main reason is that legged locomotion is more adaptable to a wide range of terrain types as the robot can decompose its path into a sequence of footholds and can use different locomotion strategies. In order to accomplish most of the locomotion tasks the...
We present a framework for quadrupedal locomotion over highly challenging terrain where the choice of appropriate footholds is crucial for the success of the behaviour. We use a path planning approach which shares many similarities with the results of the DARPA Learning Locomotion challenge and extend it to allow more flexibility and increased robu...
Legged robots have the potential to navigate in challenging terrain, and thus to exceed the mobility of wheeled vehicles. However, their control is more difficult as legged robots need to deal with foothold computation, leg trajectories and posture control in order to achieve successful navigation. In this paper, we present a new framework for the...
This paper presents a framework developed to increase the autonomy and versatility of a large (~75kg) hydraulically actuated quadrupedal robot. It combines onboard perception with two locomotion strategies, a dynamic trot and a static crawl gait. This way the robot can perceive its environment and arbitrate between the two behaviours according to t...
This paper presents the vision of the recently launched project AGILITY that aims to join forces across Europe to bring robots with legs and arms into highly unstructured outdoor environment such as a disaster area. Building upon state of the art torque controllable quadrupedal robots, we jointly investigate environment perception, motion planning,...
Legged robots have the potential to navigate in more challenging terrain than wheeled robots do. Unfortunately, their control is more difficult because they have to deal with the traditional mapping and path planning problems, as well as foothold computation, leg trajectories and posture control in order to achieve successful navigation. Many param...
We present a mobile robot whose goal is to autonomously explore an unknown indoor environment and to build a semantic map containing high-level information similar to those extracted by humans. This information includes the rooms, their connectivity, the objects they contain and the material of the walls and ground. This robot was developed in orde...
In this article we present a new approach for object recognition in a robotic underwater context. Color is an attractive feature because of its simplicity and its robustness to scale changes, object positions and partial occlusions. Unfortunately, in the underwater medium, the colors are modified by attenuation and are not constant with the distanc...
We address the problem of simultaneous localization and mapping by combining visual loop-closure detection with metrical information given by the robot odometry. The proposed algorithm builds in real-time topo-metric maps of an unknown environment, with a monocular or omnidirectional camera and odometry gathered by motors encoders. A dedicated impr...
The human perception of the external world appears as a natural, immediate and effortless task. It is achieved through a number of “low-level” sensory-motor processes that provide a high-level representation adapted to complex reasoning and decision. Compared to these representations, mobile robots usually provide only low-level obstacle maps that...
We present an approach to multi-objective exploration whose goal is to autonomously explore an unknown indoor environment. Our objective is to build a semantic map containing high-level information, namely rooms and the objects laid in these rooms. This approach was developed for the Panoramic and Active Camera for Object Mapping (PACOM) 1 project...
We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loop-closure detection method based on bags of visual words [A. Angeli, D. Filliat, S. Doncieux and J.-A. Meyer,
IEEE Transact...
This paper proposes a new method for recognition of geometrical shapes (such as lines, circles or ellipsoids) in an image. The main idea is to transform the problem into a bounded error estimation problem and then to use an interval-based method which is robust with respect to outliers. The approach is illustrated on an image taken by an underwater...
A novel pre-processing filter is proposed for underwater image restoration. Because of specific transmission properties of light in the water, underwater image suffers from limited range,non uniform lighting, low contrast, color diminished, important blur… Today pre-processing methods typically only concentrates on non uniform lighting or color cor...
A novel pre-processing filter is proposed for underwater image restoration. Because of specific transmission properties of light in the water, underwater image suffers from limited range,non uniform lighting, low contrast, color diminished, important blur... Today pre-processing methods typically only concentrates on non uniform lighting or color c...
With the development of autonomous underwater vehicles, the identification of underwater objects continues as a major issue. Because of specific properties of light in water particularly the absorption phenomenon, underwater imaging suffers from low contrast, from diminished colours and often from prominent green or blue colour. Today, object ident...
A novel pre-processing filter is proposed for underwater image restoration. Because of specific transmission properties of light in the water, underwater image suffers from limited range, non uniform lighting, low contrast, color diminished, important blur. . .Today preprocessing methods typically only concentrates on non uniform lighting or color...