Abstract: This paper describes advancement in color edge detection, using a dedicated Geometric Algebra (GA) co-processor implemented on an Application Specific Integrated Circuit (ASIC). GA provides a rich set of geometric operations, giving the advantage that many signal and image processing operations become straightforward and the algorithms intuitive to design. The use of GA allows images to be represented with the three R, G, B color channels defined as a single entity, rather than separate quantities. A novel custom ASIC is proposed and fabricated that directly targets GA operations and results in significant performance improvement for color edge detection. Use of the hardware described in this paper also shows that the convolution operation with the rotor masks within GA belongs to a class of linear vector filters and can be applied to image or speech signals. The contribution of the proposed approach has been demonstrated by implementing three different types of edge detection schemes on the proposed hardware. The overall performance gains using the proposed GA Co-Processor over existing software approaches are more than 3.2× faster than GAIGEN and more than 2800× faster than GABLE. The performance of the fabricated GA co-processor is approximately an order of magnitude faster than previously published results for hardware implementations.
Abstract: Motion detection and tracking is a relevant problem for mobile robots during navigation to avoid collisions in dynamic environments or in applications where service robots interact with humans. This paper presents a simple method to distinguish mobile obstacles from the environment that is based on applying fuzzy threshold selection to consecutive two-dimensional (2D) laser scans previously matched with robot odometry. The proposed method has been tested with the Auriga-α mobile robot in indoors to estimate the motion of nearby pedestrians.
Abstract: The problem of motion planning of an autonomous vehicle amidst other vehicles on a straight road is considered. Traffic in a number of countries is unorganized, where the vehicles do not move within predefined speed lanes. In this paper, we formulate a mechanism wherein an autonomous vehicle may travel on the “wrong” side in order to overtake a vehicle. Challenges include assessing a possible overtaking opportunity, cooperating with other vehicles, partial driving on the “wrong” side of the road and safely going to and returning from the “wrong” side. The experimental results presented show vehicles cooperating to accomplish overtaking manoeuvres.
Abstract: Buildings are important elements of cities for VANETs, since these obstacles may attenuate communications between vehicles. Consequently, the impact of buildings has to be considered as part of the attenuation model in VANET simulations of urban scenarios. However, the more elaborated the model, the more information needs to be processed during the simulation, which implies longer processing times. This complexity in simulations is not always worth it, because simplified channel models occasionally offer very accurate results. We compare three approaches to model the impact of buildings in the channel model of simulated VANETs in two urban scenarios. The simulation results for our evaluation scenarios of a traffic-efficiency application indicate that modeling the influence of buildings in urban areas as the total absence of communication between vehicles gives similar results to modeling such influence in a more realistic fashion and could be considered a conservative bound in the performance metrics.
Abstract: Turning grand concepts such as the Internet of Things (IoT) and Smart Cities into reality requires the development and deployment of a wide variety of computing devices incorporated into the Internet infrastructure. Unsupervised sensing is the cornerstone capability that these devices must have to perform useful functions, while also having low cost of acquisition and ownership, little energy consumption and a small footprint. Impedimetric sensing systems based on the so-called single-frequency DFT detectors possess many of these desirable attributes and are often introduced in remote monitoring and wearable devices. This study presents new methods of improving performance of such detectors. It demonstrates that the main source of systematic errors is the discontinuous test phasor causing the crosstalk between the in-phase and quadrature outputs and the leakage of the input signal. The study derives expressions for these errors as a function of the number of samples and operating frequency, and provides methods for correction. The proposed methods are applied to the operation of a practical device—a network analyzer integrated circuit AD5933—and discussed in detail. These methods achieve complete elimination of leakage errors and expansion of the low limit of the operation frequency range by nearly two decades without additional hardware.