Mitigating Spatial Interference in a Scalable Robot Recycling System

The initial aim of this project was to address the issue of spatial interference between robots in a robotic recycling system. The main potential bene�t of the proposed robotic recycling system is scalability. The underlying concept is that a swarm of robots process an incoming stream of materials, sorting them into homogeneous clusters of material which can then be quickly bagged and removed. When installed for a large centre, the number of robots would be correspondingly large. However, when installed for a smaller centre - such as a remote community in Newfoundland & Labrador - the number of robots, and therefore the cost of the system would be much lower. The robots themselves would constitute the system, with the additional minimal requirements of an unstructured floor space in which to operate and some input from users to help classify the input materials. A previous Harris Centre / MMSB project to explore this system made some headway, but di�culties were encountered in developing an appropriate set of robots to support further experiments. While the aim of this project was to address the issue of spatial interference, it was found that much more work was required to develop appropriate robots that could transport proxy materials (coloured pucks), classify them, navigate, and exhibit su�cient endurance for meaningful experiments. Therefore, the focus of this project switched to the development of a robot platform with these desired characteristics. It is important to note that the robots under discussion are intended for laboratory experiments using coloured pucks as proxies for real-world recyclables. A transition to robots capable of dealing with real-world conditions is far outside the project's scope. The main outcome is a robot platform called the BuPiGo which will facilitate our own experiments as well as others who are interested in swarm robotics and other distributed robotic approaches. The BuPiGo �lls a key gap in terms of the robots available to researchers. It is not intended to be a product, but an open platform that is easily extensible and makes use of widely available low-cost computing technologies such as the Raspberry Pi and Arduino platforms. It also incorporates an omnidirectional camera system to allow visual navigation between points of interest (e.g. the input point of a recycling facility and the designated output points for sorted materials). We are hopeful that this platform will now allow us to move beyond the development of experimental hardware to develop a complete model of a recycling facility using the concepts described above. This model is a �rst step towards a real-world scalable recycling facility that would allow remote communities in Newfoundland & Labrador to implement local recycling centres that would minimize transport costs and demonstrate commitment to innovation and sustainability

SWARM INTELLIGENCE AND STIGMERGY: ROBOTIC IMPLEMENTATION OF FORAGING BEHAVIOR

Swarm intelligence in multi-robot systems has become an important area of research within collective robotics. Researchers have gained inspiration from biological systems and proposed a variety of industrial, commercial, and military robotics applications. In order to bridge the gap between theory and application, a strong focus is required on robotic implementation of swarm intelligence. To date, theoretical research and computer simulations in the field have dominated, with few successful demonstrations of swarm-intelligent robotic systems. In this thesis, a study of intelligent foraging behavior via indirect communication between simple individual agents is presented. Models of foraging are reviewed and analyzed with respect to the system dynamics and dependence on important parameters. Computer simulations are also conducted to gain an understanding of foraging behavior in systems with large populations. Finally, a novel robotic implementation is presented. The experiment successfully demonstrates cooperative group foraging behavior without direct communication. Trail-laying and trail-following are employed to produce the required stigmergic cooperation. Real robots are shown to achieve increased task efficiency, as a group, resulting from indirect interactions. Experimental results also confirm that trail-based group foraging systems can adapt to dynamic environments

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

Cooperative transport in swarm robotics. Multi object transportation

Swarm robotics is a research field inspired from the natural behavior of ants, bees or fish in their natural habitat. Each group display swarm behavior in different ways. For example, ants use pheromones to trace one another in order to find a nest, reach a food source or do any operation, while bees use dance moves to attract one another to the desired place. In swarm robotics, small robots attempt to mimic insect behavior. The robotic swarm group collaborate to perform a task and collectively solve a given problem. In the process, the robots use the sensors they are equipped with to move, communicate or avoid obstacles until they collectively do the desired functionality. In this thesis, we propose a modification to the Robotic Darwinian Particle Swarm Optimization (RDPSO) algorithm. In the RDPSO, robots deployed in a rescue operation, transport one object at a time to a desired safe place. In our algorithm, we simultaneously transport multiple objects to safety. We call our algorithm Multi Robotics Darwinian Particle Swarm Optimization (MRDPSO). Our algorithm is developed and implemented on a VREP simulator using ePuck robots as swarm members. We test our algorithm using two different environment sizes complete with obstacles. First implementation is for two simultaneous object transported but can be extended to more than two. We compare our new algorithm to the results of single RDPSO and found our algorithm to be 35 to 41 % faster. We also compared our results to those obtained from three selected papers that are Ghosh, Konar, and Janarthanan [1], TORABI [2], and Kube and Bonabeau [3]. The performance measures we compare to are the accuracy of transporting all objects to desired location, and the time efficiency of transporting all the objects in our new system

ReSCon '09, Research Student Conference: Book of Abstracts

The second SED Research Student Conference (ReSCon2009) was hosted over three days, 22-24 June 2009, in the Lecture Centre at Brunel University. The conference consisted of technical presentations, a poster session and social events. The abstracts and presentations were the result of ongoing research by postgraduate research students from the School of Engineering and Design at Brunel University. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Improving Robot Team's performance by Passing Objects between Robots

Department of Computer Science and EngineeringA transport robot system is a robotic system in which robots move objects from one place to another place. Most existing transport robot systems perform three tasks: loading an item, moving to another location, and unloading the item. Traditional mobile robots, which carry objects one at a time, is not suitable for repeatedly transporting objects over a long distance. Therefore, in the factory or warehouse environment, they still use conveyor belts to transport a large number of objects. However, the existing conveyor belts are physically fixed in their environments, and it is difficult to reconfigure the layout of a conveyor network. In this thesis, I presente three new robotic systems that have the ability to pass objects at a distance between mobile robots. These three robotic systems are mobile conveyor belts, dynamic robot chains, and mobile workstations. First, conveyor belts are commonly used to transport many objects rapidly and effectively. I present a novel conveyor system called a mobile conveyor line that can autonomously organize itself to transport objects to a given location. In this thesis, I analyze the reachability of multiple mobile conveyor belts and present an algorithm to verify the reachability of a specified destination, as well as a way to gen- erate a configuration for connecting conveyor belts to reach the destination. The key results include a complete set of equations describing the reachable set of a mobile conveyor belt on a flat surface, which leads to an effective probabilistic strategy for autonomous configuration. The results of the experiment demonstrated the overlap effect, which states that reachable sets frequently overlap. This system can be suitable for locations where it is difficult to install a conveyor line, such as disaster zones. Second, I present to use mobile conveyor belts in foraging tasks in environments with obstacles. Foraging robots can form a dynamic robot chain network that can quickly send resources received from other foraging robots to a collecting zone called a depot area. A robot chain is essentially a sequence of mobile robots with the ability to quickly pass resources at a long distance. A dynamic robot chain network is a network of robot chains that allow the branches of the robot chains to connect multiple resource clusters. By allowing branching, the traffic near the end of the robot chain network can be dis- tributed to several branches, and congestion can be avoided. The dynamic robot chain network leverages mobility to relocate, reduce collection time for other robots, and quickly send resources received from other foraging robots to the depot area. The key result is the formation of robot chains capable of over- coming the two major limitations of existing dynamic depot foraging systems: the long travel distance for delivery and congestion near the central collection zone. In the experiments, given the same num- ber of robots, a dynamic robot chain network outperformed existing dynamic depots in multiple-place foraging problems. Third, I consider the idea of mobile workstations, which integrate mobile platforms with production machinery to improve efficiency by overlapping production time and delivery time. I describe a task planning algorithm for multiple mobile workstations and offer a model of mobile workstations and their jobs. This planning problem for mobile workstations includes the features of both traveling salesman problems (TSP) and job shop scheduling problems (JSP). For planning, I presente two algorithms: a) a complete search algorithm that offers a minimum makespan plan and b) a local search in the space of task graphs to offer suboptimal plans quickly. According to the experiments, the second algorithm can generate near-optimal temporal plans when the number of jobs is small. In addition, the second algorithm can generate noticeably shorter plans than a version of the job shop scheduling algorithm and SGPlan 5 when the number of jobs is large. This research shows that transport robot systems could work together with other robots or machines in various environments to overcome the limitations of existing systems for the environments. A mobile conveyor line can pass quickly objects at a long distance and can apply to many different environments by overcoming the existing problem of conveyor belts. By using mobile conveyor belts, the robots have the ability to pass objects at a distance between mobile robots to improve the performance of foraging tasks by overcoming the long travel distance for delivery and congestion near the central collection zone. In addition, a mobile workstation can handle the tasks that transport the production of goods to users. By paralleling the production time and the movement, a mobile workstation can substantially shorten the time it takes to deliver products to customers.ope

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

Accelerated Object Tracking with Local Binary Features

Multi-object tracking is a problem with wide application in modern computing. Object tracking is leveraged in areas such as human computer interaction, autonomous vehicle navigation, panorama generation, as well as countless other robotic applications. Several trackers have demonstrated favorable results for tracking of single objects. However, modern object trackers must make significant tradeoffs in order to accommodate multiple objects while maintaining real-time performance. These tradeoffs include sacrifices in robustness and accuracy that adversely affect the results. This thesis details the design and multiple implementations of an object tracker that is focused on computational efficiency. The computational efficiency of the tracker is achieved through use of local binary descriptors in a template matching approach. Candidate templates are matched to a dictionary composed of both static and dynamic templates to allow for variation in the appearance of the object while minimizing the potential for drift in the tracker. Locality constraints have been used to reduce tracking jitter. Due to the significant promise for parallelization, the tracking algorithm was implemented on the Graphics Processing Unit (GPU) using the CUDA API. The tracker\u27s efficiency also led to its implantation on a mobile platform as one of the mobile trackers that can accurately track at faster than realtime speed. Benchmarks were performed to compare the proposed tracker to state of the art trackers on a wide range of standard test videos. The tracker implemented in this work has demonstrated a higher degree of accuracy while operating several orders of magnitude faster