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Vector Field Histogram
In robotics, Vector Field Histogram (VFH) is a real time motion planning algorithm proposed by Johann Borenstein and Yoram Koren in 1991. The VFH utilizes a statistical representation of the robot's environment through the so-called histogram grid, and therefore places great emphasis on dealing with uncertainty from sensor and modeling errors. Unlike other obstacle avoidance algorithms, VFH takes into account the dynamics and shape of the robot, and returns steering commands specific to the platform. While considered a local path planner, i.e., not designed for global path optimality, the VFH has been shown to produce near optimal paths. The original VFH algorithm was based on previous work on Virtual Force Field, a local path-planning algorithm. VFH was updated in 1998 by Iwan Ulrich and Johann Borenstein, and renamed VFH+ (unofficially "Enhanced VFH"). The approach was updated again in 2000 by Ulrich and Borenstein, and was renamed VFH*. VFH is currently one of the most popul ...
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Robotics
Robotics is an interdisciplinary branch of computer science and engineering. Robotics involves design, construction, operation, and use of robots. The goal of robotics is to design machines that can help and assist humans. Robotics integrates fields of mechanical engineering, electrical engineering, information engineering, mechatronics, electronics, bioengineering, computer engineering, control engineering, software engineering, mathematics, etc. Robotics develops machines that can substitute for humans and replicate human actions. Robots can be used in many situations for many purposes, but today many are used in dangerous environments (including inspection of radioactive materials, bomb detection and deactivation), manufacturing processes, or where humans cannot survive (e.g. in space, underwater, in high heat, and clean up and containment of hazardous materials and radiation). Robots can take any form, but some are made to resemble humans in appearance. This is claim ...
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Sonar
Sonar (sound navigation and ranging or sonic navigation and ranging) is a technique that uses sound propagation (usually underwater, as in submarine navigation) to navigation, navigate, measure distances (ranging), communicate with or detect objects on or under the surface of the water, such as other vessels. "Sonar" can refer to one of two types of technology: ''passive'' sonar means listening for the sound made by vessels; ''active'' sonar means emitting pulses of sounds and listening for echoes. Sonar may be used as a means of acoustic location and of measurement of the echo characteristics of "targets" in the water. Acoustic location in air was used before the introduction of radar. Sonar may also be used for robot navigation, and SODAR (an upward-looking in-air sonar) is used for atmospheric investigations. The term ''sonar'' is also used for the equipment used to generate and receive the sound. The acoustic frequencies used in sonar systems vary from very low (infrasonic ...
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Motion Planning
Motion planning, also path planning (also known as the navigation problem or the piano mover's problem) is a computational problem to find a sequence of valid configurations that moves the object from the source to destination. The term is used in computational geometry, computer animation, robotics and computer games. For example, consider navigating a mobile robot inside a building to a distant waypoint. It should execute this task while avoiding walls and not falling down stairs. A motion planning algorithm would take a description of these tasks as input, and produce the speed and turning commands sent to the robot's wheels. Motion planning algorithms might address robots with a larger number of joints (e.g., industrial manipulators), more complex tasks (e.g. manipulation of objects), different constraints (e.g., a car that can only drive forward), and uncertainty (e.g. imperfect models of the environment or robot). Motion planning has several robotics applications, such ...
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Heuristic
A heuristic (; ), or heuristic technique, is any approach to problem solving or self-discovery that employs a practical method that is not guaranteed to be optimal, perfect, or rational, but is nevertheless sufficient for reaching an immediate, short-term goal or approximation. Where finding an optimal solution is impossible or impractical, heuristic methods can be used to speed up the process of finding a satisfactory solution. Heuristics can be mental shortcuts that ease the cognitive load of making a decision. Examples that employ heuristics include using trial and error, a rule of thumb or an educated guess. Heuristics are the strategies derived from previous experiences with similar problems. These strategies depend on using readily accessible, though loosely applicable, information to control problem solving in human beings, machines and abstract issues. When an individual applies a heuristic in practice, it generally performs as expected. However it can alternatively cre ...
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A* Search Algorithm
A* (pronounced "A-star") is a graph traversal and path search algorithm, which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. One major practical drawback is its O(b^d) space complexity, as it stores all generated nodes in memory. Thus, in practical travel-routing systems, it is generally outperformed by algorithms which can pre-process the graph to attain better performance, as well as memory-bounded approaches; however, A* is still the best solution in many cases. Peter Hart, Nils Nilsson and Bertram Raphael of Stanford Research Institute (now SRI International) first published the algorithm in 1968. It can be seen as an extension of Dijkstra's algorithm. A* achieves better performance by using heuristics to guide its search. Compared to Dijkstra's algorithm, the A* algorithm only finds the shortest path from a specified source to a specified goal, and not the shortest-path tree from a specified source to all possi ...
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Low-pass Filter
A low-pass filter is a filter that passes signals with a frequency lower than a selected cutoff frequency and attenuates signals with frequencies higher than the cutoff frequency. The exact frequency response of the filter depends on the filter design. The filter is sometimes called a high-cut filter, or treble-cut filter in audio applications. A low-pass filter is the complement of a high-pass filter. In optics, high-pass and low-pass may have different meanings, depending on whether referring to frequency or wavelength of light, since these variables are inversely related. High-pass frequency filters would act as low-pass wavelength filters, and vice versa. For this reason it is a good practice to refer to wavelength filters as ''short-pass'' and ''long-pass'' to avoid confusion, which would correspond to ''high-pass'' and ''low-pass'' frequencies. Low-pass filters exist in many different forms, including electronic circuits such as a hiss filter used in audio, anti-aliasing fil ...
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Hysteresis
Hysteresis is the dependence of the state of a system on its history. For example, a magnet may have more than one possible magnetic moment in a given magnetic field, depending on how the field changed in the past. Plots of a single component of the moment often form a loop or hysteresis curve, where there are different values of one variable depending on the direction of change of another variable. This history dependence is the basis of memory in a hard disk drive and the remanence that retains a record of the Earth's magnetic field magnitude in the past. Hysteresis occurs in ferromagnetic and ferroelectric materials, as well as in the deformation of rubber bands and shape-memory alloys and many other natural phenomena. In natural systems it is often associated with irreversible thermodynamic change such as phase transitions and with internal friction; and dissipation is a common side effect. Hysteresis can be found in physics, chemistry, engineering, biology, and economics. I ...
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Laser Rangefinder
A laser rangefinder, also known as a laser telemeter, is a rangefinder that uses a laser beam to determine the distance to an object. The most common form of laser rangefinder operates on the time of flight principle by sending a laser pulse in a narrow beam towards the object and measuring the time taken by the pulse to be reflected off the target and returned to the sender. Due to the high speed of light, this technique is not appropriate for high precision sub-millimeter measurements, where triangulation and other techniques are often used. Pulse The pulse may be coded to reduce the chance that the rangefinder can be jammed. It is possible to use Doppler effect techniques to judge whether the object is moving towards or away from the rangefinder, and if so, how fast. Precision The precision of the instrument is determined by the rise or fall time of the laser pulse and the speed of the receiver. One that uses very sharp laser pulses and has a very fast detector can rang ...
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Occupancy Grid
Occupancy Grid Mapping refers to a family of computer algorithms in probabilistic robotics for mobile robots which address the problem of generating maps from noisy and uncertain sensor measurement data, with the assumption that the robot pose is known. Occupancy grids were first proposed by H. Moravec and A. Elfes in 1985. The basic idea of the occupancy grid is to represent a map of the environment as an evenly spaced field of binary random variables each representing the presence of an obstacle at that location in the environment. Occupancy grid algorithms compute approximate posterior estimates for these random variables. Algorithm outline There are four major components of occupancy grid mapping approach. They are: * Interpretation * Integration * Position estimation * Exploration Occupancy grid mapping algorithm The goal of an occupancy mapping algorithm is to estimate the posterior probability over maps given the data: p(m\mid z_, x_), where m is the map, z_ is the set of m ...
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Motion Planning
Motion planning, also path planning (also known as the navigation problem or the piano mover's problem) is a computational problem to find a sequence of valid configurations that moves the object from the source to destination. The term is used in computational geometry, computer animation, robotics and computer games. For example, consider navigating a mobile robot inside a building to a distant waypoint. It should execute this task while avoiding walls and not falling down stairs. A motion planning algorithm would take a description of these tasks as input, and produce the speed and turning commands sent to the robot's wheels. Motion planning algorithms might address robots with a larger number of joints (e.g., industrial manipulators), more complex tasks (e.g. manipulation of objects), different constraints (e.g., a car that can only drive forward), and uncertainty (e.g. imperfect models of the environment or robot). Motion planning has several robotics applications, such ...
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Player Project
The Player Project (formerly the Player/Stage Project) is a project to create free software for research into robotics and sensor systems. Its components include the ''Player'' network server and the ''Stage'' robot platform simulators. Although accurate statistics are hard to obtain, Player is one of the most popular open-source robot interfaces in research and post-secondary education. Most of the major intelligent robotics journals and conferences regularly publish papers featuring real and simulated robot experiments using Player and Stage. Overview The Player Project is an umbrella under which two robotics-related software projects are currently developed. These include the Player networked robotics server, and the Stage 2D robot simulation environment. The project was founded in 2000 by Brian Gerkey, Richard Vaughan and Andrew Howard at the University of Southern California at Los Angeles, and is widely used in robotics research and education. It releases its software un ...
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Dynamic Window Approach
In robotics motion planning, the dynamic window approach is an online collision avoidance strategy for mobile robots developed by Dieter Fox, Wolfram Burgard, and Sebastian Thrun in 1997. Unlike other avoidance methods, the dynamic window approach is derived directly from the dynamics of the robot, and is especially designed to deal with the constraints imposed by limited velocities and accelerations of the robot. It consists of two main components, first generating a valid search space, and second selecting an optimal solution in the search space. In Fox et al. the search space is restricted to safe circular trajectories that can be reached within a short time interval and are free from collisions. The optimization goal is to select a heading and velocity that brings the robot to the goal with the maximum clearance from any obstacle. References External links Dynamic Window Approach pseudo-code and explanation Robot control 1997 in robotics {{Robo-stub ...
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