Sonar sensing for low-cost indoor mobility

Lawitzky, Gisbert; Feiten, Wendelin; Möller, M.

doi:10.1016/0921-8890(94)00026-x

Cited by 20 publications

(6 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Using a single, central emitter eliminated the possibility of conflicting echo signals, which could have occurred if two emitters were used. Having two receivers separated by a distance allows detected objects to be located in a planar environment by determining the distance between the object and each sensor (Feiten et al 1994;Lawitsky et al 1995). By angling the wide-field receivers outward two overlapping receptive fields were created (Bank 2002a(Bank , 2002b.…”

Section: Design Of the Ultrasonic Sensor Podmentioning

confidence: 99%

Animal-Inspired Sensing for Autonomously Climbing or Avoiding Obstacles

Lewinger

Harley

Watson

et al. 2009

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

The way that natural systems navigate their environments with agility, intelligence and efficiency is an inspiration to engineers. Biological attributes such as modes of locomotion, sensory modalities, behaviours and physical appearance have been used as design goals. While methods of locomotion allow robots to move through their environment, the addition of sensing, perception and decision making are necessary to perform this task with autonomy. This paper contrasts how the addition of two separate sensing modalities -tactile antennae and non-contact sensing -and a low-computation, capable microcontroller allow a biologically abstracted mobile robot to make insect-inspired decisions when encountering a shelflike obstacle, navigating a cluttered environment without collision and seeking vision-based goals while avoiding obstacles.

show abstract

Section: Design Of the Ultrasonic Sensor Podmentioning

confidence: 99%

Animal-Inspired Sensing for Autonomously Climbing or Avoiding Obstacles

Lewinger

Harley

Watson

et al. 2009

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

show abstract

“…Kalman filtering is used to determine the correct position of a robot, with an approximation given by dead reckoning and ultrasonic measurements [23], [24]. Several ultrasonic sensors can be used (one in sending mode and the others in reception mode) in order to obtain more information [25]. More information on the received ultrasonic wave (amplitude in [26], complete signal in [27]) can be taken into account to determine a more precise environmental layout.…”

Section: The Localization Problemmentioning

confidence: 99%

Localization and control of a rehabilitation mobile robot by close human-machine cooperation

Hoppenot

Colle

2001

IEEE Trans. Neural Syst. Rehabil. Eng.

View full text Add to dashboard Cite

In the field of rehabilitation robotics, a mobile personal robot represents an attractive solution, especially in economic terms in comparison with a desktop workstation. A manipulator arm mounted on a mobile robot can facilitate the restoration of the disabled user's manipulative function. In order both to encourage the person to participate in the task at hand and to be cost effective, close human-machine cooperation is essential. The person controls the robot via a remote station and develops strategies to successfully carry out a mission. The main problems encountered by the person during the execution of a mission are electing to change modes, and the mode transition itself. We have examined two aspects of this cooperation: 1) information exchange between human and machine for decision-making and 2) giving to operators complementary and redundant modes to command the system. An experiment has been conducted to study these two aspects. This paper focuses on the control of robot movements in an indoor environment and especially on localization parameters, human-like robot behavior, and the value of proposing complementary control modes to the operator.

show abstract

“…Kalman filter is used to find the position of the robot with an approximate position given by the odometry 11 . Several ultrasonic sensors (one emitter and several receivers) can be used to obtain more information 12 . A Kalman filter is also used to find the position of the robot.…”

Section: Absolute Localisationmentioning

confidence: 99%

“…11 Several ultrasonic sensors (one emitter and several receivers) can be used to obtain more information. 12 A Kalman filter is also used to find the position of the robot. Bozma proposed to analyse the wave amplitude to build a more precise map of the environment.…”

Section: Absolute Localisationmentioning

confidence: 99%

Off-line localisation of a mobile robot using ultrasonic measurements

2000

View full text Add to dashboard Cite

Regarding assistance to disabled people for object manipulation and carrying, the paper focuses on the localisation for mobile robot autonomy. In order to respect strong low-cost constraints, the perception system of the mobile robot uses sensors of low metrological quality, ultrasonic ring and odometry. That poses new problems for localisation, in particular. Among different localisation techniques, we present only off-line localisation. With poor perception means, it is necessary to introduce a priori knowledge on sensors and environment models. To solve the localisation problem, the ultrasonic image is segmented applying the Hough transform, well-adapted to ultrasonic sensor characteristics. The segments are then matched with the room, modelled and assumed to be rectangular. Several positions are found. A first sort, based on a cost function, reduces the possibilities. The remaining ambiguities are removed by a neural network which plays the part of a classifier detecting the door in the environment. Improvements of the method are proposed to take into account obstacles and non-rectangular room. Experimental results show that the localisation operates even with one obstacle.

show abstract

Sonar sensing for low-cost indoor mobility

Cited by 20 publications

References 9 publications

Animal-Inspired Sensing for Autonomously Climbing or Avoiding Obstacles

Animal-Inspired Sensing for Autonomously Climbing or Avoiding Obstacles

Localization and control of a rehabilitation mobile robot by close human-machine cooperation

Off-line localisation of a mobile robot using ultrasonic measurements

Contact Info

Product

Resources

About