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45
Issues in Evolutionary Robotics
, 1992
"... In this paper we propose and justify a methodology for the development of the control systems, or `cognitive architectures', of autonomous mobile robots. We argue that the design by hand of such control systems becomes prohibitively difficult as complexity increases. We discuss an alternative a ..."
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Cited by 272 (33 self)
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In this paper we propose and justify a methodology for the development of the control systems, or `cognitive architectures', of autonomous mobile robots. We argue that the design by hand of such control systems becomes prohibitively difficult as complexity increases. We discuss an alternative approach, involving artificial evolution, where the basic building blocks for cognitive architectures are adaptive noise-tolerant dynamical neural networks, rather than programs. These networks may be recurrent, and should operate in real time. Evolution should be incremental, using an extended and modified version of genetic algorithms. We nally propose that, sooner rather than later, visual processing will be required in order for robots to engage in non-trivial navigation behaviours. Time constraints suggest that initial architecture evaluations should be largely done in simulation. The pitfalls of simulations compared with reality are discussed, together with the importance of incorporating noise. To support our claims and proposals, we present results from some preliminary experiments where robots which roam office-like environments are evolved.
A fast and incremental method for loop-closure detection using bags of visual words,” Conditionally accpeted for publication in
- IEEE Transactions On Robotics, Special Issue on Visual SLAM
, 2008
"... Abstract—In robotic applications of visual simultaneous localization and mapping techniques, loop-closure detection and global localization are two issues that require the capacity to recognize a previously visited place from current camera measurements. We present an online method that makes it pos ..."
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Cited by 69 (6 self)
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Abstract—In robotic applications of visual simultaneous localization and mapping techniques, loop-closure detection and global localization are two issues that require the capacity to recognize a previously visited place from current camera measurements. We present an online method that makes it possible to detect when an image comes from an already perceived scene using local shape and color information. Our approach extends the bag-of-words method used in image classification to incremental conditions and relies on Bayesian filtering to estimate loop-closure probability. We demonstrate the efficiency of our solution by real-time loop-closure detection under strong perceptual aliasing conditions in both indoor and outdoor image sequences taken with a handheld camera. Index Terms—Loop-closure detection, localization, SLAM. I.
Map-based navigation in mobile robots - II. A review of map-learning and path-planning strategies
, 2003
"... This article reviews map-learning and path-planning strategies within the context of map-based navigation in mobile robots. Concerning map-learning, it distinguishes metric maps from topological maps and describes procedures that help maintain the coherency of these maps. Concerning path-planning, i ..."
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Cited by 39 (11 self)
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This article reviews map-learning and path-planning strategies within the context of map-based navigation in mobile robots. Concerning map-learning, it distinguishes metric maps from topological maps and describes procedures that help maintain the coherency of these maps. Concerning path-planning, it distinguishes continuous from discretized spaces and describes procedures applicable when the execution of a plan fails. It insists on the need for an integrated conception of such procedures, that must be tightly tailored to the specific robot that is used - notably to the capacities and limitations of its sensory-motor equipment - and to the specific environment that is experienced. A hierarchy of navigation strategies is outlined in the discussion, together with the sort of adaptive capacities each affords to cope with unexpected obstacles or dangers encountered on an animat or robot's way to its goal.
A contribution to vision-based autonomous helicopter flight in urban environments
- Robotics and Autonomous Systems
, 2005
"... A navigation strategy that exploits the optic flow and inertial information to continuously avoid collisions with both lateral and frontal obstacles has been used to control a simulated helicopter flying autonomously in a textured urban environment. Experimental results demonstrate that the correspo ..."
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Cited by 37 (4 self)
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A navigation strategy that exploits the optic flow and inertial information to continuously avoid collisions with both lateral and frontal obstacles has been used to control a simulated helicopter flying autonomously in a textured urban environment. Experimental results demonstrate that the corresponding controller generates cautious behavior, whereby the helicopter tends to stay in the middle of narrow corridors, while its forward velocity is automatically reduced when the obstacle density increases. When confronted with a frontal obstacle, the controller is also able to generate a tight U-turn that ensures the UAV’s survival. The paper provides comparisons with related work, and discusses the applicability of the approach to real platforms. Key words: Helicopter, optic flow, obstacle-avoidance, urban environment Airborne devices are specific platforms whose control raises distinctive difficulties as compared to ground robots. For instance, they can hardly rely upon usual sensors to navigate, especially if the challenge is to let them move in an urban environment – because infra-red sensors are sensitive to external light
Path formation in a robot swarm -- Self-organized strategies to find your way home
, 2008
"... We present two swarm intelligence control mechanisms used for distributed robot path formation. In the first, the robots form linear chains. We study three variants of robot chains, which vary in the degree of motion allowed to the chain structure. The second mechanism is called vectorfield. In thi ..."
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Cited by 34 (18 self)
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We present two swarm intelligence control mechanisms used for distributed robot path formation. In the first, the robots form linear chains. We study three variants of robot chains, which vary in the degree of motion allowed to the chain structure. The second mechanism is called vectorfield. In this case, the robots form a pattern that globally indicates the direction towards a goal or home location. We test each controller on a task that consists in forming a path between two objects which an individual robot cannot perceive simultaneously. Our simulation experiments show promising results. All the controllers are able to form paths in complex obstacle environments and exhibit very good scalability, robustness, and fault tolerance characteristics. Additionally, we observe that chains perform better for small robot group sizes, while vectorfield performs better for large groups.
Self-organised path formation in a swarm of robots
- SWARM INTELL (2011 ) 5 : 97–119
, 2011
"... In this paper, we study the problem of exploration and navigation in an unknown environment from an evolutionary swarm robotics perspective. In other words, we search for an efficient exploration and navigation strategy for a swarm of robots, which exploits cooperation and self-organisation to cop ..."
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Cited by 20 (8 self)
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In this paper, we study the problem of exploration and navigation in an unknown environment from an evolutionary swarm robotics perspective. In other words, we search for an efficient exploration and navigation strategy for a swarm of robots, which exploits cooperation and self-organisation to cope with the limited abilities of the individual robots. The task faced by the robots consists in the exploration of an unknown environment in order to find a path between two distant target areas. The collective strategy is synthesised through evolutionary robotics techniques, and is based on the emergence of a dynamic structure formed by the robots moving back and forth between the two target areas. Due to this structure, each robot is able to maintain the right heading and to efficiently navigate between the two areas. The evolved behaviour proved to be effective in finding the shortest path, adaptable to new environmental conditions, scalable to larger groups and larger environment size, and robust to individual failures.
Global Localization and Topological Map-Learning for Robot Navigation
, 2002
"... This paper describes a navigation system implemented on a real mobile robot. Using simple sonar and visual sensors, it makes possible the autonomous construction of a dense topological map representing the environment. At any time during the mapping process, this system is able to globally localize ..."
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Cited by 20 (8 self)
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This paper describes a navigation system implemented on a real mobile robot. Using simple sonar and visual sensors, it makes possible the autonomous construction of a dense topological map representing the environment. At any time during the mapping process, this system is able to globally localize the robot, i.e. to estimate the robot's position even if the robot is passively moved from one place to another within the mapped area. This is achieved using algorithms inspired by Hidden Markov Models adapted to the on-line building of the map. Advantages and drawbacks of the system are discussed, along with its potential implications for the understanding of biological navigation systems.
A.: The Psikharpax project: Towards building an artificial rat. Robotics and Autonomous Systems 50(4
, 2005
"... Drawing inspiration from biology, the Psikharpax project aims at endowing a robot with a sensori-motor equipment and a neural control architecture that will afford some of the capacities of autonomy and adaptation that are exhibited by real rats. The paper summarizes the current state of achievement ..."
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Cited by 18 (12 self)
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Drawing inspiration from biology, the Psikharpax project aims at endowing a robot with a sensori-motor equipment and a neural control architecture that will afford some of the capacities of autonomy and adaptation that are exhibited by real rats. The paper summarizes the current state of achievement of the project. It successively describes the robot’s future sensors and actuators, and several biomimetic models of the anatomy and physiology of structures in the rat’s brain, like the hippocampus and the basal ganglia, which have already been at work on various robots, and that make navigation and action selection possible. Preliminary results on the implementation of learning mechanisms in these structures are also presented. Finally, the article discusses the potential benefits that a biologically-inspired approach affords to traditional autonomous robotics.
Interactive learning of visual topological navigation
"... Abstract — We present a topological navigation system that is able to visually recognize the different rooms of an apartment and guide a robot between them. Specifically tailored for small entertainment robots, the system relies on vision only and learns its navigation capabilities incrementally by ..."
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Cited by 17 (11 self)
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Abstract — We present a topological navigation system that is able to visually recognize the different rooms of an apartment and guide a robot between them. Specifically tailored for small entertainment robots, the system relies on vision only and learns its navigation capabilities incrementally by interacting with a user. This continuous learning strategy makes the system particularly adaptable to environmental lighting and structure modifications. From the computer vision point of view, the system uses a purely appearance-based image representation called bag of visual words, without any metric information. This representation was adapted to the incremental context of robotics and supplemented by active perception to enhance performances. Empirical validation on real robots and on the publicly available INDECS image database are presented. I.
