Enhancing Cognitive Assistance Systems with Inertial Measurement Units

Günthner, W. A.

doi:10.1007/978-3-540-76997-2

Cited by 9 publications

(11 citation statements)

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“…The simplifying assumption in the general case is that the terrain traversed by the robot is horizontal and flat, and usually pavement characteristics such as surface types, and other and anomalies are neglected. This, however, is not the case in outdoor environments, where the terrain's topography and surface types have a major bearing on the robots displacement and navigation, and should be carefully considered This paper describes the use of a powerful, yet simple, precise and efficient technique known as CF 10,5 to tackle the localization problem for mobile robots navigating on uneven terrains in outdoor environments. For our discussion, we cluster the typical irregularities found in outdoor environments into three classes:…”

Section: → (T) = [X(t) Y(t) ψ(T)]mentioning

confidence: 99%

Adaptive complementary filtering algorithm for mobile robot localization

Neto¹,

Macharet²,

Campos³

et al. 2009

J. Braz. Comp. Soc.

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As a mobile robot navigates through an indoor environment, the condition of the floor is of low (or no) relevance to its decisions. In an outdoor environment, however, terrain characteristics play a major role on the robot's motion. Without an adequate assessment of terrain conditions and irregularities, the robot will be prone to major failures, since the environment conditions may greatly vary. As such, it may assume any orientation about the three axes of its reference frame, which leads to a full six degrees of freedom configuration. The added three degrees of freedom have a major bearing on position and velocity estimation due to higher time complexity of classical techniques such as Kalman filters and particle filters. This article presents an algorithm for localization of mobile robots based on the complementary filtering technique to estimate the localization and orientation, through the fusion of data from IMU, GPS and compass. The main advantages are the low complexity of implementation and the high quality of the results for the case of navigation in outdoor environments (uneven terrain). The results obtained through this system are compared positively with those obtained using more complex and time consuming classic techniques.

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Section: → (T) = [X(t) Y(t) ψ(T)]mentioning

confidence: 99%

Adaptive complementary filtering algorithm for mobile robot localization

Neto¹,

Macharet²,

Campos³

et al. 2009

J. Braz. Comp. Soc.

View full text Add to dashboard Cite

show abstract

“…Inertial Measurement Units found on flight control boards are classified as MEMS (Micro-Electromechanical Systems) devices, which are small three dimensional structures produced on a silicon substrate through the use of various chemical processes. [13].…”

Section: Inertial Measurement Unitmentioning

confidence: 99%

“…The operating principles of a typical MEMS gyroscope rely on a "tuning fork" structure as seen in Figure 2.13. Figure 2.13: Operating Principle of MEMS Gyroscope [13] This structure relies on the oscillation of the two masses m in the center of each fork as the object rotates about ω. The rotation generates a force described in equation 2.5, where a is the acceleration of the mass, ω is the angular rage, and v is the mass velocity:…”

Section: Gyroscopementioning

confidence: 99%

“…The displacement of the masses during rotation is sensed with a capacitive comb structure, where the displacement corresponds to an angular rate. This type of MEMS structure can be used to detect the angular changes for both the pitch and roll directions of the quadcopter [13]. A single suspended mass is used in conjunction with four capacitors arranged in a grid.…”

Section: Gyroscopementioning

confidence: 99%

“…The relationship between the voltage and distance between the plates can be seen in equation 2.6, where Q is the electric charge, ∆C is the change in capacitance, ∆d is the change in distance between the plates, is the dielectric constant, and A is the capacitive plate area [13]. When the sensor is accelerated vertically, the distance between all four capacitors changes at the same rate due to the uniform motion of the suspended mass.…”

Section: Gyroscopementioning

confidence: 99%

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