A method of controlling machine pose using sensor fusion includes receiving, with at least one processor, from each of a plurality of Inertial Measurement Units (IMU's) mounted on different components of the machine, a time series of signals indicative of acceleration and angular rate of motion measurements for each of the components of the machine on which one or more of the plurality of IMU's are mounted, and from at least one non-IMU sensor, a signal indicative of at least one of position, velocity, or acceleration of at least one of the machine components, a position, velocity, or acceleration of any potential obstacles or other features at a job site where the machine is operating, or an operator input. For each one of the IMU's on a separate component of the machine, the signals received from the IMU are fused with a separate Kalman filter module by combining an acceleration measurement and an angular rate of motion measurement from the IMU to estimate an output joint angle for the component of the machine on which the IMU is mounted. Estimated and measured values of the output joint angle for the component in successive timesteps are combined, a kinematic equation is solved to determine a real time value for at least one of position, velocity, and acceleration of the machine component at successive timesteps, and the determined real time value is applied in an implementation of a controlled operational movement of the machine component in a successive time step to a position and orientation resulting in at least one of an improvement in machine footing, machine stability, productivity based on positioning of a machine component, reliability based on positioning of a machine component, and efficiency of the machine operations as compared to an operational movement of each machine component in a previous time step before the application of the determined real time value.

The present invention is related to detecting location of a navigation device using sensor data analysis, where the sensor is coupled to the navigation device. A hierarchical algorithm is used for making a series of decisions regarding the location of the navigation device, with each decision corresponding to a class among a plurality of classes related to the possible motion modes and/or precise location of the device, including the location of the device with respect to a person's body. By accurately identifying the device location, the hierarchical algorithm facilitates in providing relevant contextual information, thereby enhancing situational awareness.

Technologies for determining a user's location by a mobile computing device include detecting, based on sensed inertial characteristics of the mobile computing device, that a user of the mobile computing device has taken a physical step in a direction. The mobile computing device determines a directional heading of the mobile computing device in the direction and a variation of an orientation of the mobile computing device relative to a previous orientation of the mobile computing device at a previous physical step of the user based on the sensed inertial characteristics. The mobile computing device further applies a Kalman filter to determine a heading of the user based on the determined directional heading of the mobile computing device and the variation of the orientation and determines an estimated location of the user based on the user's determined heading, an estimated step length of the user, and a previous location of the user at the previous physical step.

Described herein is a device for detecting the attitude of motor vehicles, which comprises using at least one filter of a complementary type for computing an estimate ({circumflex over (x)}.sub.i) of angles of attitude (, , ) of the motor vehicle as a function of input signals comprising an acceleration signal (A) and an angular-velocity signal (). According to the invention, the device (10) comprises a plurality of complementary filters (12.sub.1, . . . , 12.sub.n) each tuned for operating in a specific dynamic range, and a supervisor unit (11), that acts to recognize the dynamic range of the input signals (A, ) and select a corresponding filter (12.sub.i) from said plurality of complementary filters (12.sub.1, . . . , 12.sub.n).

A method of processing signals from an accelerometer/gyroscopic-based input device includes providing the input device within a vehicle. An accelerometer/gyroscopic-based second device is also provided within the vehicle. The input device is manually actuated while the vehicle is in motion. First signals are transmitted from the input device in response to the manually actuating step. Second signals are transmitted from the second device in response to the motion of the vehicle. The first signals are adjusted dependent upon the second signals.

An air data computer senses acceleration and rotational rate of an aircraft with an inertial sensor assembly of the air data computer. The air data computer determines first attitude information of the aircraft based on the acceleration and rotational rate sensed with the inertial sensor assembly. The air data computer receives second attitude information of the aircraft from a source external to the air data computer, and determines attitude correction values based on the first attitude information and the second attitude information. The air data computer applies the attitude correction values to the first attitude information to produce error-corrected attitude information that is output from the air data computer.

A method of controlling a mobile platform includes measuring a distance between the mobile platform and an object at each of a plurality of positions of the mobile platform, and determining a position of the object based on results of measuring the distance.

Systems and methods for producing two independent dissimilar attitude solutions, two independent dissimilar inertial solutions or both from one improved navigation device are disclosed. In one embodiment, an avionics system comprises: an inertial navigation device configured to produce a first set of attitude solutions; an attitude heading and reference unit configured to produce a primary set of attitude solutions and a secondary set of attitude solutions; and a display device configured to receive the first set of attitude solutions, the primary set of attitude solutions and the secondary set of attitude solutions, wherein if the first set of attitude solutions and the primary set of attitude solutions are yielding different results, then the display device is configured to determine whether the first set of attitude solutions or the primary set of attitude solutions is correct by determining differences between the attitude solutions and determining which difference is below a threshold.

A method for real-time calibration of a gyroscope, configured for supplying a value of angular velocity that is function of a first angle of rotation about a first angular-sensing axis that includes defining a time interval, acquiring from an accelerometer an equivalent value of angular velocity that can be associated to the first angle of rotation; calculating a deviation between the value of angular velocity and the equivalent value of angular velocity; iteratively repeating the previous steps through the time interval, incrementing or decrementing an offset variable by a first predefined value on the basis of the values assumed by the deviations during the iterations, and updating the value of angular velocity as a function of the offset variable.

Methods, apparatus, and systems are provided for calibrating an optical flow (OF) sensor by using an inertial measurement unit (IMU) measurements in a planar robot system.