Instrumental conditioning is a psychological process whereby an animal learns to associate its actions with their consequences. This type of learning is exploited in animal training techniques such as ''shapin...
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ISBN:
(纸本)0819426415
Instrumental conditioning is a psychological process whereby an animal learns to associate its actions with their consequences. This type of learning is exploited in animal training techniques such as ''shaping by successive approximations'', which enables trainers to gradually adjust the animal's behavior by giving strategically timed reinforcements. While this is similar in principle to reinforcement learning, the real phenomenon includes many subtle effects not considered in the machine learning literature, In addition, a good deal of domain information is utilized by an animal learning a new task;it does not start from scratch every time it learns a new behavior. For these reasons, it is not surprising that mobile robot learning algorithms have yet to approach the sophistication and robustness of animal learning. A serious attempt to model instrumental learning could prove fruitful for improving machine learning techniques. In the present paper, we develop a computational theory of shaping at a level appropriate for controlling mobile robots. The theory is based on a series of mechanisms for ''behavior editing'', in which pre-existing behaviors, either innate or previously learned, can be dramatically changed in magnitude, shifted in direction, or otherwise manipulated so as to produce new behavioral routines. We have implemented our theory on Amelia, an RWI B21 mobile robot equipped with a gripper and color video camera. We provide results from training Amelia on several tasks, all of which were constructed as variations of one innate behavior, object-pursuit.
The superb aerial performance of flying insects is achieved with comparatively simple neural machinery. We have been investigating the pathway in the locust visual system that signals the rapid approach of an object t...
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ISBN:
(纸本)0819438618
The superb aerial performance of flying insects is achieved with comparatively simple neural machinery. We have been investigating the pathway in the locust visual system that signals the rapid approach of an object towards the eye. Two identified neurons have been shown to respond selectively to the images of an object approaching the locust's eye. A neural network based on the input organisation of these neurons responds directionally when challenged with approaching and receding objects and reveals the importance of a critical race, between excitation passing down the network and inhibition directed laterally, for the rapid build-up of excitation in response to approaching objects. The strongest response is given to an object approaching on a collision course with the eye, when collision is imminent. Like the neurons, the network is tightly tuned to a collision trajectory. We have incorporated this network into the control structure of a small mobile Kephera robot using the IQR 4-21 software we developed. The network responds to looming motion and is effective at evoking avoidance manoeuvres in the robot, moving at speeds from 1-12.5cm/s. Our aim is to use the circuit as an artificial looming detector for use in moving vehicles.
New generations of modular and reconfigurable roboticsystems with many degrees of freedom can be transformed to achieve different functions, modes of manipulation, and means of mobility resulting in efficient multifu...
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New generations of modular and reconfigurable roboticsystems with many degrees of freedom can be transformed to achieve different functions, modes of manipulation, and means of mobility resulting in efficient multifunctional systems which adapt to complex environments. The design of modular distributed algorithms and architectures for control of these systems is particularly challenging since kinematic and dynamic performance must be maintained throughout a range of alternative physical reconfigurations. The `Tetrobot' is a prototype modular system using parallel, variable geometry truss-like mechanisms which can be reconfigured to create moving platforms, walking machines, manipulator arms, a pipe crawler and other devices. Modular algorithms for distributed control and dynamic redundancy resolution of these systems will be discussed, and the principles of distributed control for modular systems generalize beyond these specific mechanisms. The resulting Tetrobot system has a range of interesting applications including space robotics, construction, mining, medical, undersea, and flexible manufacturing.
RoBlock is the first phase of an internally financed project at the Institute aimed at building a system in which two industrial robots suspended from a gentry, as shown below, cooperate to perform a task specified by...
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ISBN:
(纸本)0819438618
RoBlock is the first phase of an internally financed project at the Institute aimed at building a system in which two industrial robots suspended from a gentry, as shown below, cooperate to perform a task specified by an external user, in this case, assembling an unstructured collection of coloured wooden blocks into a specified 3-dimensional pattern. The blocks are indentified and localised using computer vision and grasped with a suction cup mechanism. Future phases of the project will involve other processes such as grasping and lifting, as well as other types of robot such as autonomous vehicles or variable geometry trusses. Innovative features of the control software system include: The use of an advanced trajectory planning system which ensures collision avoidance based on a generalisation of the method of artificial potential fields [1], The use of a generic model-based controller which "learns" the values of parameters, including static and kinetic friction, of a detailed mechanical model of itself by comparing actual with planned movements [2], The use of fast, flexible, and robust pattern recognition and 3D-interpretation strategies, Integration of trajectory planning and control with the sensorsystems in a distributed Java application running on a network of PC's attached to the individual physical components. In designing this first stage, the aim was to build in the minimum complexity necessary to make the system non-trivially autonomous and to minimize the technological risks. The aims of this project, which is planned to be operational during 2000, are as follows: To provide a platform for carrying out experimental research in multi-agent systems and autonomous manufacturing systems, To test the interdisciplinary cooperation architecture of the Maersk Institute, in which researchers in the fields of applied mathematics (modelling the physical world), software engineering (modelling the system) and sensor/actuator technology (relating the virtual and
Air and ground vehicles exhibit complementary capabilities and characteristics as roboticsensor platforms. Fixed wing aircraft offer broad field of view and rapid coverage of search areas. However, minimum operating ...
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ISBN:
(纸本)0819455628
Air and ground vehicles exhibit complementary capabilities and characteristics as roboticsensor platforms. Fixed wing aircraft offer broad field of view and rapid coverage of search areas. However, minimum operating airspeed and altitude limits, combined with attitude uncertainty, place a lower limit on their ability to detect and localize ground features. Ground vehicles on the other hand offer high resolution sensing over relatively short ranges with the disadvantaue of slow coverage. This paper presents a decentralized architecture and solution methodology for seamlessly realizing the collaborative potential of air and ground roboticsensor platforms. We provide a framework based on an established approach to the underlying sensorfusion problem. This provides transparent integration of information from heterogeneous sources. An information-theoretic utility measure captures the task objective and robot inter-dependencies. A simple distributed solution mechanism is employed to determine team member sensing trajectories subject to the constraints of individual vehicle and sensor sub-systems. The architecture is applied to a mission involving searching for and localizing an unknown number of targets in an user specified search area. Results for a team of two fixed wing UAVs and two all terrain UGVs equipped with vision sensors are presented.
The American Lobster Homarus americanus is a highly mobile marine decapod, ubiquitous to the benthic environment of the eastern North Atlantic. Lobsters occupy a range of subtidal habitats on the continental shelf, an...
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ISBN:
(纸本)0819438618
The American Lobster Homarus americanus is a highly mobile marine decapod, ubiquitous to the benthic environment of the eastern North Atlantic. Lobsters occupy a range of subtidal habitats on the continental shelf, and are capable of navigating through spatially complex boulder fields, as well as coping with variable water currents. Given these competencies, we have adopted the lobster as a design model for a biomimetic autonomous underwater vehicle intended for operation in similar environments. A central motor pattern generator model was developed from electromyographic data from lobsters, and is being implemented on an eight-legged ambulatory vehicle. The vehicle uses Nitinol shape-memory alloy wires as linear actuators, physically modeling the antagonistic muscle pairs of a lobster leg. The contraction of the wires is produced by heating them with an electrical current. This produces a change in the crystalline structure of the material from a martensite to an austenite state, resulting in a 5% contraction of the wire. Three pairs of wires are used around three joints to produce a three-degrees-of-freedom walking leg. Current drivers power the actuators, and pulse-width modulation is used to obtain graded contractions from the muscles. The combination of a biologically based control system coupled with a linear actuator sharing many characteristics of invertebrate muscle tissue has enabled us to construct a biomimetic ambulatory robot sharing some of the competencies of the model.
As the complexity of the missions to planetary surfaces increases, so too does the need for autonomous rover systems. This need is complicated by the power, mass and computer storage restrictions on such systems (Mill...
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As the complexity of the missions to planetary surfaces increases, so too does the need for autonomous rover systems. This need is complicated by the power, mass and computer storage restrictions on such systems (Miller, Proceedings SPIE Conference on Cooperative Intelligent robotics in Space III, 1829, pp. 472-475, 1992). To address these problems, we have recently developed a system called BISMARC (Biologically Inspired System for Map-based Autonomous Rover control) for planetary missions involving multiple small, lightweight surface revers (Huntsberger, Proceedings SPIE Symposium on sensorfusion and decentralizedcontrol in Autonomous roboticsystems, pp. 221-227, 1997). BISMARC is capable of cooperative planetary surface retrieval operations such as a multiple cache recovery mission to Mars. The system employs autonomous navigation techniques, behavior-based control for surface retrieval operations, and an action selection mechanism based on a modified form of free flow hierarchy (Rosenblatt and Payton, Proceedings IEEE/INNS Joint Conference on Neural Networks, pp. 317-324, 1989). This paper primarily describes the navigation and map-mapping subsystems of BISMARC. They are inspired by some recent studies of London taxi drivers indicating that the right hippocampal region of the brain is activated for path planning but not for landmark identification (Maguire et al., Journal of Neuroscience, 17, 7103-7110, 1997). We also report the results of some experimental studies of simulated navigation in planetary environments. (C) 1998 Elsevier Science Ltd. All rights reserved.
A wide variety of tactile (touch) sensors exist today for robotics and related applications. They make use of various transduction methods, smart materials and engineered structures, complex electronics, and sophistic...
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A wide variety of tactile (touch) sensors exist today for robotics and related applications. They make use of various transduction methods, smart materials and engineered structures, complex electronics, and sophisticated data processing. While highly useful in themselves, effective utilization of tactile sensors in robotics applications has been slow to come and largely remains elusive today. This paper surveys the state of the art and the research issues in this area, with the emphasis on effective utilization of tactile sensors in roboticsystems. One specific with the use of tactile sensing in robotics is that the sensors have to be spread along the robot body, the way the human skin is -thus dictating varied 3-D spatio-temporal requirements, decentralized and distributed control, and handling of multiple simultaneous tactile contacts. Satisfying these requirements pose challenges to making tactile sensor modality a reality. Overcoming these challenges requires dealing with issues such as sensors placement, electronic/mechanical hardware, methods to access and acquire signals, automatic calibration techniques, and algorithms to process and interpret sensing data in real time. We survey this field from a system perspective, recognizing the fact that the system performance tends to depend on how its various components are put together. It is hoped that the survey will be of use to practitioners designing tactile sensing hardware (whole-body or large-patch sensor coverage), and to researchers working on cognitive robotics involving tactile sensing.
While significant recent progress has been made in development of mobile robots for planetary surface exploration, there remain major challenges. These include increased autonomy of operation, traverse of challenging ...
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ISBN:
(纸本)0819438618
While significant recent progress has been made in development of mobile robots for planetary surface exploration, there remain major challenges. These include increased autonomy of operation, traverse of challenging terrain, and fault-tolerance under long, unattended periods of use. We have begun work which addresses some of these issues, with an initial focus on problems of "high risk access," that is, autonomous roving over highly variable, rough terrain. This is a dual problem of sensing those conditions which require rover adaptation, and controlling the rover actions so as to implement this adaptation in a well understood way (relative to metrics of rover stability, traction, power utilization, etc.). Our work progresses along several related technical lines: 1) development a fused state estimator which robustly integrates internal rover state and externally sensed environmental information to provide accurate "configuration" information;2) kinematic and dynamical stability analysis of such configurations so as to determine "predicts" for a needed change of control regime (e.g., traction control, active c.g. positioning, rover shoulder stance/pose);3) definition and implementation of a behavior-based control architecture and action-selection strategy which autonomously sequences multi-level rover controls and reconfiguration. We report on these developments, both software simulations and hardware experimentation. Experiments include reconfigurable control of JPL's Sample Return Rover geometry and motion during its autonomous traverse over simulated Mars terrain.
This paper describes recent efforts to develop integrated multi-sensor payloads for small robotic platforms for improved operator situational awareness and ultimately for greater robot autonomy. The focus is on enhanc...
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ISBN:
(纸本)9780819468949
This paper describes recent efforts to develop integrated multi-sensor payloads for small robotic platforms for improved operator situational awareness and ultimately for greater robot autonomy. The focus is on enhancements to perception through integration of electro-optic, acoustic, and other sensors for navigation and inspection. The goals are to provide easier control and operation of the robot through fusion of multiple sensor outputs, to improve interoperability of the sensor payload package across multiple platforms through the use of open standards and architectures, and to reduce integration costs by embedded sensor data processing and fusion within the sensor payload package. The solutions investigated in this project to be discussed include: improved capture, processing and display of sensor data from multiple, non-commensurate sensors;an extensible architecture to support plug and play of integrated sensor packages;built-in health, power and system status monitoring using embedded diagnostics/prognostics;sensor payload integration into standard product forms for optimized size, weight and power;and the use of the open Joint Architecture for Unmanned systems (JAUS)/Society of Automotive Engineers (SAE) AS-4 interoperability standard. This project is in its first of three years. This paper will discuss the applicability of each of the solutions in terms of its projected impact to reducing operational time for the robot and teleoperator.
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