Multi-Agent Pathfinding with Matching using Enhanced Partial Expansion A*

For the Multi-Agent Pathfinding (MAPF) problem, a set of non-colliding paths must be found for multiple agents. In Multi-Agent Pathfinding with Matching (MAPFM), this problem is extended: agents and goals are added to a team and each agent has to navigate to a goal that belongs to the same team. In this paper, two extensions of the EPEA* MAPF...

Solving Multi-Agent Pathfinding with Matching using A*+ID+OD

This paper extends the Multi-Agent Pathfinding (MAPF) algorithm, A*+ID+OD, to be able to solve problems with matching. This extension still keeps the optimal and completeness properties of the original algorithm. Matching is added to the algorithm in both an exhaustive and heuristic manner. Exhaustive matching is further improved by adding a new...

Improving Ultrawide Band Ranging Using Two Antennas

Ultrawideband technology can be used to measure the distance between two device equipped with ultrawideband transceivers. Multiple ultrawideband devices known as anchors can localize a device that supports ultrawideband communication after each anchor measures the distance between itself and the device. The anchor and the tag can measure the...

Multi-model inference on the edge: Scheduling for multi-model execution on resource constrained devices

Deep neural networks (DNNs) are becoming the core components of many applications running on edge devices,especially for image-based analysis, e.g., identifying objects, faces, and genders. While very successful in resource rich environments like the cloud of powerful computers, utilizing Deep Learning on edge devices for inference is not used...

Investigating Non-Work-Conserving Scheduling in Event-Driven Real-Time Systems

Embeddedreal-time systems that have cost or energy constraints are usually limited inprocessing power and memory. This limitation typically leads to applyingsimpler execution models such as non-preemptive scheduling. A problem with anon-preemptive real-time system is that finding a schedule without causingdeadline misses is...

Modeling Inference Time of Deep Neural Networks on Memory-constrained Systems

Deep neural networks have revolutionized multiple fields within computer science. It is important to have a comprehensive understanding of the memory requirements and performance of deep networks on low-resource systems. While there have been efforts to this end, the effects of severe memory limits and heavy swapping are understudied. We have...

Offline Compression of Convolutional Neural Networks on Edge Devices

Edge Devices and Artificial Intelligence are important and ever increasing fields in technology. Yet their combination is lacking because the neural networks used in AI are being made increasingly large and complex while edge devices lack the resources to keep up with these developments. Neural network model compression will allow these edge...

Detection and Tracking of a Fast-Moving Object in Squash using a Low-Cost Approach

Advancement in technology has given rise to the need for technology to be utilized in extracting meaningful game-play information from sports. To do so in a ball-game like squash, the prime objective is to perform ball-tracking in an adequate and efficient manner. In squash, ball-tracking is complex due to the small size of the ball, the high...

Novel Interaction Method for UHF RFID Tags

RFID technology is slowly replacing traditional bar codes as a way to identify and track objects and individuals. However, consumer-oriented market penetration has been limited as dedicated RFID readers carry a high start-up cost. Furthermore, interactions with individual tags require special-purpose RFID readers. We present a novel RFID tag...

3D Gradient Printing of Energetic Multi-Materials

The performance of gun and rocket propellants, which consist of energetic materials, is largely determined by their geometry and composition. Con- ventional production methods limit the performance by putting constraints on both. With additive manufacturing, or 3D-printing, there are signi- cantly fewer geometry constraints and together with the...

Command Recognition on Intermittently-Powered Devices

The Internet of Things (IoT) is expected to include billions of tiny devices that collect, process, and communicate sensory data. As of now, batteries power these devices. Batteries, however, are large, expensive, and short-lived - even the rechargeable ones wear out in a few years. Therefore, they are not a sustainable powering solution. Tiny...

Design and implementation of a LoRa based Gateway

The project focuses on the hardware-software co design of a LoRaWAN based industrial IoT gateway used for proprietary applications. Long Range Wide Area Network, abbreviated as LoRaWAN is a network and data layer running over the LoRa PHY layer which operates at 868 MHz[29]. The surge in LoRa has led big market players like SemTech to licence...