This study evaluates a trajectory generation method for the efficient navigation of autonomous mobile robots in forests. We propose a graph-based cycle generation method. A graph was generated using ...environmental landmarks as nodes, and the graph was modified to be Eulerian. The Hamiltonian cycle contained nodes that could be regarded as the midpoint between a pair of landmarks; an efficient path could then be found. We applied this method to an artificial forest to verify the feasibility.
Analysis of large data sets is increasingly important in business and scientific research. One of the challenges in such analysis stems from uncertainty in data, which can produce anomalous results. ...This paper proposes a method for detecting an anomaly in time series data using a Support Vector Machine (SVM). Three different kernels of the SVM are analyzed to predict anomalies in the UCR time series benchmark data sets. Comparison of the three kernels shows that the defined parameter values of the Radial Basis Function (RBF) kernel are critical for improving the validity and accuracy in anomaly detection. Our results show that the RBF kernel of the SVM can be used to advantage in detecting anomalies.
The evolution of complexity is one of the prime features of life on Earth. Although well accepted as the product of adaptation, the dynamics underlying the evolutionary build-up of complex adaptive ...systems remains poorly resolved. Using simulated robot swarms that exhibit ant-like group foraging with trail pheromones, we show that their self-organizing capacity paradoxically involves regulatory behavior that arises in advance. We focus on a traffic rule on their foraging trail as a regulatory trait. We allow the simulated robot swarms to evolve pheromone responsiveness and traffic rules simultaneously. In most cases, the traffic rule, initially arising as selectively neutral component behaviors, assists the group foraging system to bypass a fitness valley caused by overcrowding on the trail. Our study reveals a hitherto underappreciated role of regulatory mechanisms in the origin of complex adaptive systems, as well as highlights the importance of embodiment in the study of their evolution.
There is a growing demand for automation by robots in the home replacement meal industry due to labor shortages in food factories and from the perspective of the SDGs1. In this research, we are ...developing autonomous work robots that can perform home replacement meal tasks and developing the technology for industrial food automation using Artificial Intelligence (AI) to improve productivity, security, and safety. In this paper, we perform weight estimation of the served object to identify the amount of spaghetti grasped by the robot. We created our dataset of spaghetti used for weight estimation. Spaghetti of varying weight is in different types of containers, placed at random positions in the robot workspace. The proposed model is shown to estimate the weight of spaghetti with an error of at most 10%.
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