SLAM in large indoor environments with low-cost, noisy, and sparse sonars

Yap, Teddy N.; Shelton, Christian R.

doi:10.1109/robot.2009.5152192

Cited by 41 publications

(28 citation statements)

References 16 publications

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“…Maps can be refined by improving feature detection of SONAR transducer [9], [10]. Another method of enhancing results is by the fusion of SONAR with vision [11], or with laser range finders [12], [13].…”

Section: Demerits and Limitationsmentioning

confidence: 99%

An Economic Simultaneous Localization and Mapping System for Remote Mobile Robot Using SONAR and an Innovative AI Algorithm

Saleem¹

2013

IJFCC

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Abstract-This paper proposes an economic and effective approach towards the simultaneous localization and mapping of a mobile rescue robot using a single ultrasonic range finder. The procedure eliminates the complication involved with localizing the robot in a map while creating the map simultaneously, by employing a novel control mechanism. The problem is solved by separating the mapping and localization processes and merging the outputs after specific intervals. The data from sensory devices is processed wirelessly to map the surroundings of the robot on a computer. The innovative AI algorithm extends the map cognitively as subsequent data is acquired. Moreover, a comparison is made between conventional methodologies and the one presented in this paper along with possible enhancements applicable. Using this architecture, the economic cost, computational power and time required for SLAM are significantly reduced. The design was utilized on a mobile rescue robot for the RoboCup competitions.

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Section: Demerits and Limitationsmentioning

confidence: 99%

An Economic Simultaneous Localization and Mapping System for Remote Mobile Robot Using SONAR and an Innovative AI Algorithm

Saleem¹

2013

IJFCC

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“…Various sensors are used for observing an environment, such as sonar [1,21], laser [22], and vision [23][24][25]. The robot constructs a map of the environment by exploration, and the robot can use the constructed map to navigate toward a specific location in the map.…”

Section: Related Workmentioning

confidence: 99%

Pebbles: User-Configurable Device Network for Robot Navigation

Ishii

et al. 2013

Lecture Notes in Computer Science

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Abstract. This study proposes devices suitable for use by non-experts to design robot navigation routes. The user places landmarks, called pebbles, on the floor to tell navigation routes to a robot. Using infrared communication, the pebbles automatically generate navigation routes. The system is designed such that nonexpert users can understand the system status to configure the user's target environment without expert assistance. During deployment, the system provides LED and voice feedback. The user can confirm that the devices are appropriately placed for the construction of a desired navigation network. In addition, because there is a device at each destination, our method can name locations by associating a device ID with a particular name. A user study showed that nonexpert users were able to understand device usage and construct robot navigation routes.

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“…Yap et al [4] also used sonar sensors. They worked with the ActivMedia P3-DX robot, which has less sensors than SCITOS A5.…”

Section: Related Workmentioning

confidence: 99%

Affordable SLAM through the co-design of hardware and methodology

Magnenat

Longchamp

Bonani

et al. 2010

2010 IEEE International Conference on Robotics and Automation

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Abstract-Simultaneous localization and mapping (SLAM) is a prominent feature for autonomous robots operating in undefined environments. Applications areas such as consumer robotics appliances would clearly benefit from low-cost and compact SLAM implementations. The SLAM research community has developed several robust algorithms in the course of the last two decades. However, until now most SLAM demonstrators have relied on expensive sensors or large processing power, limiting their realms of application. Several works have explored optimizations into various directions; however none has presented a global optimization from the mechatronic to the algorithmic level.In this article, we present a solution to the SLAM problem based on the co-design of a slim rotating distance scanner, a lightweight SLAM software, and an optimization methodology. The scanner consists of a set of infrared distance sensors mounted on a contactless rotating platform. The SLAM algorithm is an adaptation of FastSLAM 2.0 that runs in real time on a miniature robot. The optimization methodology finds the parameters of the SLAM algorithm using an evolution strategy.This work demonstrates that an inexpensive sensor coupled with a low-speed processor are good enough to perform SLAM in simple environments in real time.

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SLAM in large indoor environments with low-cost, noisy, and sparse sonars

Cited by 41 publications

References 16 publications

An Economic Simultaneous Localization and Mapping System for Remote Mobile Robot Using SONAR and an Innovative AI Algorithm

An Economic Simultaneous Localization and Mapping System for Remote Mobile Robot Using SONAR and an Innovative AI Algorithm

Pebbles: User-Configurable Device Network for Robot Navigation

Affordable SLAM through the co-design of hardware and methodology

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