Abstract: The present invention presents a sensing system 1 and a corresponding method for detecting moving objects 11 in the surroundings of a vehicle 10. The sensing system 1 comprises an imaging unit 2 for obtaining an image stream 2a, a computing unit 3 for analyzing the image stream 2a, and a control unit 4 for controlling the vehicle 10 based on the analysis result of the computing unit 3. The sensing system 1 particularly employs a background-model-free estimation. The sensing system 1 is configured to perform a local analysis of two neighboring motion vectors 6, which are computed from points 7a in images 5a, 5b of the image stream 2a, and to determine, whether the points 7a corresponding to these motion vectors 6 belong to a particularly moving object.

Abstract: The present invention proposes a profound user-mower interaction, which enables the user to teach a robotic lawn mower for improving its visual obstacle detection. The main idea of the invention is that the user can show some typical obstacles from his garden to the mower. This will increases the performance of the visual obstacle detection. In the simplest scenario the user just places the mower in front of an obstacle, and activates the learning mechanism of the classification means (module) of the mower. The increasing use of smart devices such as smart phones or tablets enables also more elaborated learning. For example, the mower can send the input image to the smart device, and the user can provide a detailed annotation of the image. This will drastically improve the learning, because the mower is provided with ground truth information.

Abstract: One embodiment of the present invention provides a method for supporting the development of a parallel/distributed application, wherein the development process comprises a design phase, an implementation phase and a test phase. A script language can be provided in the design phase for representing elements of a connectivity graph and the connectivity between them. In the implementation phase, modules can be provided for implementing functionality of the application, executors can be provided for defining a type of execution for the modules, and process-instances can be provided for distributing the application over several computing devices. In the test phase, abstraction levels can be provided for monitoring and testing the application.

Abstract: A supporting head is provided with binaural artificial ears. Each binaural artificial ear comprises an auricle-shaped structure and a microphone. In order to enhance auditory localization cues, at least an upper part of the head is provided with an acoustically dampening surface.

Abstract: A computer-implemented method for setting-up and operating a driver assistance system, the method comprising the steps of: visually sensing the environment of a vehicle, sensing at least one rate of change of a parameter representing a status of the car, which parameter can be influenced by a driver manipulating a man/machine interface of the vehicle, structuring information gathered by the visual sensing by classifying the at least one sensed rate of change in different categories, in order to find visual features associated to a certain category of sensed rate of change and thus associated with a certain behavior of the driver.

Abstract: The invention proposes a method for imitation-learning of movements of a robot, wherein the robot performs the following steps: observing a movement of an entity in the robot's environment, recording the observed movement using a sensorial data stream and representing the recorded movement in a different task space representations, selecting a subset of the task space representations for the imitation learning and reproduction of the movement to be imitated.

Abstract: The present invention provides an Advanced Driver Assistant System (ADAS) 10 and an operating method thereof, which work on long time scales, and guide an ego vehicle 20 away from upcoming risks, rather than only reacting to risks to mitigate the consequences of a crash. To this end, information comprising the orientation of other traffic participants 30, 40, 50, 60, a free driving area of the ego vehicle 20, and/or a driving trajectory of the vehicle 20 as intended by the driver is taken into account, in order to determine potential risks.

Abstract: The invention proposes a method for detecting dynamic objects in the scene in a driver assistance system of a vehicle, comprising the steps of: feeding signals from sensors (internal sensors, 3D sensors, cameras) of the vehicle to the driver assistance system, generation of a surrounding model using 3D world positions based on the sensor signals and, combination of 3D Warping-based approaches and optical flow based approaches, whose gained novel key points are: a) Restriction of the search space of an optical flow method based on the computation results of the 3D warping method, b) Additionally, to a) also an optimal parameterization of the optical flow approach in terms of search direction, amplitude, etc., c) Refinement and verification of the detection results of one of the methods based on the computation results of the other method (if both approaches are running in parallel), storing the detected dynamic objects and their measured motion parameters for their use in, e.g.

Abstract: The invention presents a method for analyzing speech in a spoken dialog system, comprising the steps of: accepting an utterance by at least one means for accepting acoustical signals, in particular a microphone, analyzing the utterance and obtaining prosodic cues from the utterance using at least one processing engine, wherein the utterance is evaluated based on the prosodic cues to determine a prominence of parts of the utterance, and wherein the utterance is analyzed to detect at least one marker feature, e.g. a negative statement, indicative of the utterance containing at least one part to replace at least one part in a previous utterance, the part to be replaced in the previous utterance being determined based on the prominence determined for the parts of the previous utterance and the replacement parts being determined based on the prominence of the parts in the utterance, and wherein the previous utterance is evaluated with the replacement part(s).

Abstract: This invention is in the field of machine learning and neural associative memory. In particular the invention discloses a neural associative memory structure for storing and maintaining associations between memory address patterns and memory content patterns using a neural network, as well as methods for storing and retrieving such associations. Bayesian learning is applied to achieve non-linear learning.

Abstract: Efficiently simulating an Amari dynamics of a neural field a, the Amari dynamics being specified by the equation (1) where a(x,t) is the state of the neural field a, represented in a spatial domain (SR) using coordinates x,t, i(x,i) is a function stating the input to the neural field at time t, f[.] is a bounded monotonic transfer function having values between 0 and 1, F(x) is an interaction kernel, ? specifies the time scale on which the neural field a changes and h is a constant specifying the global excitation or inhibition of the neural field a. A method comprises the step of simulating an application of the transfer function f to the neural field a. Simulating an application of the transfer function f comprises smoothing the neural field a by applying a smoothing operator (S).

Abstract: The invention refers to a method for controlling the effector trajectory from a current state to a target state. First invariant control parameters of the trajectory are determined. The effector trajectory is then represented in a task description being void of the invariant control parameters. The effector trajectory is controlled on the basis of this task description. The invention further refers to a method for controlling the effector trajectory wherein the effector trajectory is calculated by mapping increments from a control parameter space on a configuration space. The dimensional difference between the configuration space and the control parameter space leaves redundant degrees of freedom of a Null space. The degrees of freedom of the Null space are increased using a task description being void of invariant control parameters.

Abstract: The present invention presents a method and system for an autonomous mower attached with a camera, wherein the control of the parameters of the camera and the control of the mower movement and grass detection are optimized holistically during operation. The present invention mitigates the camera sensing limits by adapting the movement speed of the mower. Furthermore, the camera control optimizes the visibility of grass by using the grass mask of a grass segmentation to calculate updated exposure, gain and aperture values only from grass pixels. The grass segmentation tracks changes in the grass color that are caused by illumination differences. Optionally, the system is equipped with a head light used to further improve the camera signal quality in conjunction with the control of the camera parameters and the movement speed of the mower.

Abstract: An anticipatory monitoring and prediction system can include methods for generating effective, accurate predictions of other traffic objects in the vicinity of an ego-car. The invention proposes to combine approximate probability distributions (ADPs) of agent states with Attractor Functions (AFs) for generating distributed probabilistic representations of the potential future states of the observed traffic objects. AFs are selected based on both the current road context, in which the ego-car is situated, and the current states of all participating objects. The generated predictions can be used to filter incoming sensory information for better object state estimations, rate the nature of the behavior of other traffic objects by comparing generated predictions with actual perceived sensor information, or infer accident likelihoods by comparing the predicted state distributions of objects and the ego-car. Warning and information signals or control commands can be issued in a driving assistance system.

Abstract: This invention is in the field of machine learning and neural associative memory. In particular the invention discloses a neural associative memory structure for storing and maintaining associations between memory address patterns and memory content patterns using a neural network, as well as methods for retrieving such associations. A method for a non-linear synaptic learning of discrete synapses is disclosed, and its application on neural networks is laid out.

Abstract: Generally the background of the present invention is the field of artificial vision systems, i.e. systems having a visual sensing means (e.g. a video camera) and a following processing stage implemented using a computing unit. The processing stage outputs a representation of the visually analysed scene, which output can then be fed to control different actors, such as e.g. parts of a vehicle (automobile, plane, . . . ) or a robot, preferably an autonomous robot such as e.g. a humanoid robot.

Abstract: The invention relates to a method for detecting the proper motion of an real-world object, comprising the steps of acquiring, by an image capturing device (ICD), a first image (I1) of the object at a first point in time (t1) and a second image (I2) at a second point in time (t2); obtaining a third (hypothetical) image (I3), based on an estimated effect of the motion of the image capturing device (ICD) itself (EMF) between the first and the second point in time (t1, t2), wherein the effect of the motion of the image capturing device (ICD) itself is estimated based on the forward kinematics of the image capturing device; determining an optical flow (OF) between the second image (I2) and the third image (I3); and evaluating the optical flow (OF) by incorporating uncertainties of the optical flow (OF) and the ego-motion-flow (EMF) in order to determine the proper motion of the object.

Abstract: A controller for the motion control of a robot, comprises: a target input interface for supplying the controller with information about a target to be reached, a predicting module predicting at least one future state of the controlled robot using an internal model of the robot, a planning module for planning future states of the robot, wherein the planning starts from a predicted state supplied from the predicting module, a reactive controller, for outputting motor commands in order to make the controlled robot reach a target, and a target arbitrator for selecting the target output by the predicting module or the output from the planning module.

Abstract: The present invention proposes a warning system that can be implemented in any kind of vehicle, in order to efficiently detect moving objects. The system utilizes at least one camera for a continuous imaging of the surroundings of the vehicle. Thereby, moving objects can be monitored. A computing unit is programmed to estimate a motion of any moving object based on a pixel motion in the camera image. If a dangerously moving object is detected, a warning unit can be used for issuing a warning signal. To take such a decision, the estimated motion of at least one of the moving objects can be correlated or compared to predetermined motion patterns.

Abstract: The invention proposes a system that uses a novel method to analyze the surface being about to be traversed by a vehicle. The system can be used to enhance vehicle safety and control. The system makes use of AER cameras such as the Silicon Retina. The Silicon Retina is used monitor the surface to be traversed, and a processing unit analyzes the surface based on the signal provided by the Silicon Retina. The proposed surface analysis method carried out by the system surpasses state-of-art analysis methods.