Denning Mobile Robot Company

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The Denning Mobile Robot Company of Boston was the first company to offer ready-made autonomous robots that were subsequently purchased primarily by researchers. Grinnell More's Real World Interface, Inc. (RWI) and James Slater's Nomadic Technologies (US), along with Francesco Mondada's K-Team (Switzerland), were other pioneering companies in this field, addressing the need for ready-made robots for use by robotics researchers. RWI created the B-21, Nomadic the XR4000, whilst the tiny Khepera mobile robot emerged from the stables of the Swiss K-Team. However, the high price of these machines meant that only a few graduate students and military researchers could afford them. Eventually, the low-cost Pioneer robot was introduced in 1995 (from a collaboration between RWI and ActivMedia Robotics), a project that expanded research in mobile robotics due to the affordable price.

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History

By 1999, the Denning company was defunct. In 1998, RWI joined with ISRobotics to form iRobot. More introduced the PackBot remote control robot, veering away from autonomous research robots to pursue military markets. Nomadic Technologies also left the field. MobileRobots Inc and K-Team continued to supply the research community.

In 2003 the Defense Advanced Research Projects Agency (DARPA) contracted with Segway to convert fifteen Segway PTs into Segway Robotic Mobility Platforms. Segway and delivered units to DARPA in April. In June DARPA worked with SPAWAR Systems Center San Diego to distribute the units to 14 government and university research institutions. [1]

Autonomous navigation techniques

An ActivMedia Pioneer 3-AT robot at the Georgia Institute of Technology ActivMedia Pioneer 3-AT robot.jpg
An ActivMedia Pioneer 3-AT robot at the Georgia Institute of Technology

Indoor operation

Research robots improved in autonomous indoor operation during the 1990s and the 2000s. Ready-made research bases offer the necessary sensing, mobility and computational power. These include the Pioneer, PatrolBot, PowerBot, and PeopleBot. These platforms can map buildings and navigate out-of-the-box, using SLAM and a variation on Monte Carlo method/Markov localization and modified value-iterated search, with any sensor of the 2-D range-finder class. This method creates a human readable map of the robot's workspace that can control and track robots as they move. Evolution Robotics offers single-camera VSLAM software, which replaces range-finding with visual pattern-matching, but this system cannot create a human-readable map. Other groups are building stereocam-based VSLAM. Because the stereo camera provides range-finding data, maps can be made and robots tracked. The K-Team Khepera, Segway-based platforms and other research robots can link to external computing resources to use such software.

Precision depends upon sensor precision, data granularity and calculation speed. Range-finding lasers may have +/-1 cm accuracy while digital stereo camera accuracy is limited to .25 pixel and thus is range-dependent. Vision-based systems require more computational resources than simple range-finding systems such as lasers, but may employ a digital signal processor embedded with the camera. Cost/precision trade-offs led to less expensive vision-based systems on consumer robots while commercial and industrial robots and automated guided vehicles (AGVs) tend to use laser-based systems.

Outdoor operation

Outdoors, localization is primarily handled with GPS, however, satellite signals can frequently be lost due to obstructions. Without a robots typically use dead reckoning and inertial motion tracking. Dead reckoning relies on relative wheel motion and is subject to cumulative slippage errors. Inertial motion tracking uses rate gyroscopes and accelerometers to measure motion. Accuracy depends upon sensor quality and calibration. The Segway RMP 400 and Seekur robots are two of the platforms designed for such research; most other outdoor research robots are jerry-rigged from existing vehicles.

In constrained outdoor areas, some robots, such as the John Deere Gator, simply surround the perimeter with radio beacons and use simple triangulation from three or more beacons to localize and navigate. Beacons are also used indoors by older AGVs in factories.

Programming

Much research software for autonomous robots is Free Software or Open Source Software, including: Robot Operating System, Carmen from Carnegie Mellon, Player/Stage/Gazebo from the University of Southern California and the ARIA APIs [2] from MobileRobots Inc. URBI with a Free Software SDK, is used in many universities.

Commercial software includes Webots, which has been developed since 1998 and is licensed by more than 500 universities. It runs on Linux, Windows and Mac OS X. In June 2006, Microsoft Research began offering free beta-test copies of a Robotics Studio software development kit with Pioneer robots in simulation for Windows XP.

Related Research Articles

<span class="mw-page-title-main">Lidar</span> Method of spatial measurement using laser scanning

Lidar is an acronym of "light detection and ranging" or "laser imaging, detection, and ranging". It is a method for determining ranges by targeting an object or a surface with a laser and measuring the time for the reflected light to return to the receiver. It is sometimes called 3-D laser scanning, a special combination of 3-D scanning and laser scanning. LIDAR has terrestrial, airborne, and mobile applications.

An autonomous robot is a robot that acts without recourse to human control. The first autonomous robots environment were known as Elmer and Elsie, which were constructed in the late 1940s by W. Grey Walter. They were the first robots in history that were programmed to "think" the way biological brains do and meant to have free will. Elmer and Elsie were often labeled as tortoises because of how they were shaped and the manner in which they moved. They were capable of phototaxis which is the movement that occurs in response to light stimulus.

Robotic mapping is a discipline related to computer vision and cartography. The goal for an autonomous robot is to be able to construct a map or floor plan and to localize itself and its recharging bases or beacons in it. Robotic mapping is that branch which deals with the study and application of ability to localize itself in a map / plan and sometimes to construct the map or floor plan by the autonomous robot.

<span class="mw-page-title-main">Simultaneous localization and mapping</span> Computational navigational technique used by robots and autonomous vehicles

Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. While this initially appears to be a chicken or the egg problem, there are several algorithms known to solve it in, at least approximately, tractable time for certain environments. Popular approximate solution methods include the particle filter, extended Kalman filter, covariance intersection, and GraphSLAM. SLAM algorithms are based on concepts in computational geometry and computer vision, and are used in robot navigation, robotic mapping and odometry for virtual reality or augmented reality.

<span class="mw-page-title-main">PatrolBot</span>

PatrolBot is a programmable autonomous general purpose service robot rover built by MobileRobots Inc. PatrolBots are manufactured in various configurations and serve as bases for companies developing delivery robots, security robots, environmental monitoring rovers, robot guides, and other indoor service robots.

<span class="mw-page-title-main">Unmanned ground vehicle</span> Type of vehicle

An unmanned ground vehicle (UGV) is a vehicle that operates while in contact with the ground and without an onboard human presence. UGVs can be used for many applications where it may be inconvenient, dangerous, or impossible to have a human operator present. Generally, the vehicle will have a set of sensors to observe the environment, and will either autonomously make decisions about its behavior or pass the information to a human operator at a different location who will control the vehicle through teleoperation.

<span class="mw-page-title-main">Stanley (vehicle)</span> Autonomous car

Stanley is an autonomous car created by Stanford University's Stanford Racing Team in cooperation with the Volkswagen Electronics Research Laboratory (ERL). It won the 2005 DARPA Grand Challenge, earning the Stanford Racing Team a $2 million prize.

<span class="mw-page-title-main">Automated guided vehicle</span> Type of portable robot

An automated guided vehicle (AGV), different from an autonomous mobile robot (AMR), is a portable robot that follows along marked long lines or wires on the floor, or uses radio waves, vision cameras, magnets, or lasers for navigation. They are most often used in industrial applications to transport heavy materials around a large industrial building, such as a factory or warehouse. Application of the automatic guided vehicle broadened during the late 20th century.

<span class="mw-page-title-main">Mobile robot</span> Type of robot

A mobile robot is an automatic machine that is capable of locomotion. Mobile robotics is usually considered to be a subfield of robotics and information engineering.

A positioning system is a system for determining the position of an object in space. One of the most well-known and commonly used positioning systems is the Global Positioning System (GPS).

<span class="mw-page-title-main">Player Project</span> Robot interface specification and software system

The Player Project creates free and open-source software for research into robotics and sensor systems. Its components include the Player network server and the Stage platform robotics 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.

<span class="mw-page-title-main">Indoor positioning system</span>

An indoor positioning system (IPS) is a network of devices used to locate people or objects where GPS and other satellite technologies lack precision or fail entirely, such as inside multistory buildings, airports, alleys, parking garages, and underground locations.

<span class="mw-page-title-main">Robot navigation</span> Robots ability to navigate

Robot localization denotes the robot's ability to establish its own position and orientation within the frame of reference. Path planning is effectively an extension of localisation, in that it requires the determination of the robot's current position and a position of a goal location, both within the same frame of reference or coordinates. Map building can be in the shape of a metric map or any notation describing locations in the robot frame of reference.

<span class="mw-page-title-main">Webots</span> Open-source robot simulator

Webots is a free and open-source 3D robot simulator used in industry, education and research.

<span class="mw-page-title-main">Mobile Robot Programming Toolkit</span>

The Mobile Robot Programming Toolkit (MRPT) is a cross-platform and open source C++ library aimed to help robotics researchers to design and implement algorithms related to Simultaneous Localization and Mapping (SLAM), computer vision and motion planning. Different research groups have employed MRPT to implement projects reported in some of the major robotics journals and conferences.

<span class="mw-page-title-main">Inertial navigation system</span> Continuously computed dead reckoning

An inertial navigation system (INS) is a navigation device that uses motion sensors (accelerometers), rotation sensors (gyroscopes) and a computer to continuously calculate by dead reckoning the position, the orientation, and the velocity of a moving object without the need for external references. Often the inertial sensors are supplemented by a barometric altimeter and sometimes by magnetic sensors (magnetometers) and/or speed measuring devices. INSs are used on mobile robots and on vehicles such as ships, aircraft, submarines, guided missiles, and spacecraft. Other terms used to refer to inertial navigation systems or closely related devices include inertial guidance system, inertial instrument, inertial measurement unit (IMU) and many other variations. Older INS systems generally used an inertial platform as their mounting point to the vehicle and the terms are sometimes considered synonymous.

CajunBot refers to the autonomous ground vehicles developed by the University of Louisiana at Lafayette for the DARPA Grand Challenges. CajunBot was featured on CNN and on the Discovery Channel science series Robocars.

<span class="mw-page-title-main">National Robotics Engineering Center</span> Operating unit within the Robotics Institute of Carnegie Mellon University

The National Robotics Engineering Center (NREC) is an operating unit within the Robotics Institute (RI) of Carnegie Mellon University. NREC works closely with government and industry clients to apply robotic technologies to real-world processes and products, including unmanned vehicle and platform design, autonomy, sensing and image processing, machine learning, manipulation, and human–robot interaction.

Alcherio Martinoli is a roboticist and an associate professor at the École polytechnique fédérale de Lausanne (EPFL) in the School of Architecture, Civil and Environmental Engineering where he heads the Distributed Systems and Algorithms Laboratory.

References

  1. "Archived copy" (PDF). Archived from the original (PDF) on 2009-12-29. Retrieved 2009-11-28.{{cite web}}: CS1 maint: archived copy as title (link)
  2. "ARIA API libraries". Archived from the original on 2008-09-15. Retrieved 2019-10-07.