Grey Decision-making for a Billiard Robot

[[abstract]]Billiard is one of the most complex games to play in the real world. A player needs to visualize the situation between balls and pockets and to score the ball into the designate pocket by his/her own experience. A billiard robot is developed to imitate the behavior of human beings to play billiard. There are machine vision, decision-making, control and actuating subsystems in the experiment setup. The objective of this paper is to design a decision algorithm for a billiard robot by using grey theory. The results indicate that the decision algorithm work very well in both the simulation and experiment.[[conferencetype]]國際[[conferencedate]]20041010~20041013[[iscallforpapers]]Y[[conferencelocation]]Hague, Netherland

Trajectory solutions for a game-playing robot using nonprehensile manipulation methods and machine vision

The need for autonomous systems designed to play games, both strategy-based and physical, comes from the quest to model human behaviour under tough and competitive environments that require human skill at its best. In the last two decades, and especially after the 1996 defeat of the world chess champion by a chess-playing computer, physical games have been receiving greater attention. Robocup TM, i.e. robotic football, is a well-known example, with the participation of thousands of researchers all over the world. The robots created to play snooker/pool/billiards are placed in this context. Snooker, as well as being a game of strategy, also requires accurate physical manipulation skills from the player, and these two aspects qualify snooker as a potential game for autonomous system development research. Although research into playing strategy in snooker has made considerable progress using various artificial intelligence methods, the physical manipulation part of the game is not fully addressed by the robots created so far. This thesis looks at the different ball manipulation options snooker players use, like the shots that impart spin to the ball in order to accurately position the balls on the table, by trying to predict the ball trajectories under the action of various dynamic phenomena, such as impacts. A 3-degree of freedom robot, which can manipulate the snooker cue on a par with humans, at high velocities, using a servomotor, and position the snooker cue on the ball accurately with the help of a stepper drive, is designed and fabricated. [Continues.

Particle Computation: Complexity, Algorithms, and Logic

We investigate algorithmic control of a large swarm of mobile particles (such as robots, sensors, or building material) that move in a 2D workspace using a global input signal (such as gravity or a magnetic field). We show that a maze of obstacles to the environment can be used to create complex systems. We provide a wide range of results for a wide range of questions. These can be subdivided into external algorithmic problems, in which particle configurations serve as input for computations that are performed elsewhere, and internal logic problems, in which the particle configurations themselves are used for carrying out computations. For external algorithms, we give both negative and positive results. If we are given a set of stationary obstacles, we prove that it is NP-hard to decide whether a given initial configuration of unit-sized particles can be transformed into a desired target configuration. Moreover, we show that finding a control sequence of minimum length is PSPACE-complete. We also work on the inverse problem, providing constructive algorithms to design workspaces that efficiently implement arbitrary permutations between different configurations. For internal logic, we investigate how arbitrary computations can be implemented. We demonstrate how to encode dual-rail logic to build a universal logic gate that concurrently evaluates and, nand, nor, and or operations. Using many of these gates and appropriate interconnects, we can evaluate any logical expression. However, we establish that simulating the full range of complex interactions present in arbitrary digital circuits encounters a fundamental difficulty: a fan-out gate cannot be generated. We resolve this missing component with the help of 2x1 particles, which can create fan-out gates that produce multiple copies of the inputs. Using these gates we provide rules for replicating arbitrary digital circuits.Comment: 27 pages, 19 figures, full version that combines three previous conference article

Modeling emotion for anthromorphic agents

Emotions should play an important role in the design of interfaces since human beings interact with machines as if they were social actors. To investigate if and how machines can express emotions, it is necessary to investigate human-human interaction. Facial expressions are one of the most powerful, natural and immediate means by which human beings communicate their emotions and intentions. Face-to-face communication is inherently natural and social for human-human interactions. There is substantial evidence that suggests this may also be true for humancomputer interactions. In other words, human beings regard computers as social agents with whom “face-to-interface” interaction may be most easy and efficacious. Based on Ekman’s theory, SIX (6) universal emotion expressions that do not change too much from culture to culture were adopted in this study. The six emotion expressions are happiness, sadness, disgust, anger, surprise and fear. In addition, based on these six universal expressions, the AeMotion system was developed using Visual Basic 6.0. The Sony Digital Handycam video camcorder was used to capture the facial expressions. The system provides meaningful information for emotion detection through human facial expression. The final result of pixelization can be transferred into the set of processing array for emotion recognition purpose. The pixel formation provides indirect information for emotion (sad, anger, disgust, happy, fear and surprise) cues such as “brows lowered and drawn together” portrays action of disgust. The study demonstrates that the human facial expressions were successfully captured and pre-process to represent image-based emotions.The study also demonstrates that the image-based parameters could be used to interpret the facial affect space. In addition, the results also demonstrate that there is a need for both basic and applied research contributions to the rapid developing field of affective computing. Currently, experiments are still being conducted to see the impact of a variety of compressed image conditions has on affect space

Logic matter : digital logic as heuristics for physical self-guided-assembly

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 123-124).Given the increasing complexity of the physical structures surrounding our everyday environment -- buildings, machines, computers and almost every other physical object that humans interact with -- the processes of assembling these complex structures are inevitably caught in a battle of time, complexity and human/machine processing power. If we are to keep up with this exponential growth in construction complexity we need to develop automated assembly logic embedded within our material parts to aid in construction. In this thesis I introduce Logic Matter as a system of passive mechanical digital logic modules for self-guided-assembly of large-scale structures. As opposed to current systems in self-reconfigurable robotics, Logic Matter introduces scalability, robustness, redundancy and local heuristics to achieve passive assembly. I propose a mechanical module that implements digital NAND logic as an effective tool for encoding local and global assembly sequences. I then show a physical prototype that successfully demonstrates the described mechanics, encoded information and passive self-guided-assembly. Finally, I show exciting potentials of Logic Matter as a new system of computing with applications in space/volume filling, surface construction, and 3D circuit assembly.by Skylar J.E. Tibbits.S.M

Intrinsic and environmental factors modulating autonomous robotic search under high uncertainty

Autonomous robotic search problems deal with different levels of uncertainty. When uncertainty is low, deterministic strategies employing available knowledge result in most effective searches. However, there are domains where uncertainty is always high since information about robot location, environment boundaries or precise reference points is unattainable, e.g., in cave, deep ocean, planetary exploration, or upon sensor or communications impairment. Furthermore, latency regarding when search targets move, appear or disappear add to uncertainty sources. Here we study intrinsic and environmental factors that affect low-informed robotic search based on diffusive Brownian, naive ballistic, and superdiffusive strategies (Lévy walks), and in particular, the effectiveness of their random exploration. Representative strategies were evaluated considering both intrinsic (motion drift, energy or memory limitations) and extrinsic factors (obstacles and search boundaries). Our results point towards minimum-knowledge based modulation approaches that can adjust distinct spatial and temporal aspects of random exploration to lead to effective autonomous search under uncertaintyThis work was supported in part by Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER), under Grants PGC2018-095895-B-I00, TIN2017-84452-R, and PID2020-114867RB-I0

Planification optimale discrète et continue : un joueur de billard autonome optimisé

Le sujet de Thèse de ce doctorat consiste en l'élaboration de méthodes pour la planification dans les domaines avec aspects continus, discrets et stochastiques. Cette classe de problème, bien qu'assez générale, ne comporte pas pour l'instant de solution efficace et est souvent traitée de façon discrète plutôt que continue afin d'y appliquer les approches existantes. L'aspect stochastique apporte une difficulté supplémentaire à la recherche d'un plan optimal, et rend le problème d'autant plus intéressant. L'ensemble des approches et méthodes proposées dans cette Thèse sont avant tout appliquées au jeu du billard, tout en gardant dans l'esprit qu'une généralisation permettrait son application à d'autres problèmes similaires. En un premier lieu, une classification de ce type de problème par rapport aux recherches existantes sera effectuée, suivie d'une courte revue des approches actuelles possiblement applicables pour la recherche d'une solution acceptable. Un modèle général développé dans le contexte du jeu du billard sera présenté, ainsi que quelques indices sur la façon de le résoudre à l'aide de la programmation dynamique. Deuxièmement, un modèle pour une approche à deux-couches sera proposé, utilisant un contrôleur robuste profitant de la finesse qui peut être exploitée des techniques d'optimisation non-linéaire. Finalement, le modèle à deux-couches sera raffiné et quelques heuristiques de planifications seront proposée, afin de guider le contrôleur de façon à déterminer un plan efficace. On terminera à l'aide d'une synThèse des résultats et une discussion sur les perspectives futures

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

On the development of slime mould morphological, intracellular and heterotic computing devices

The use of live biological substrates in the fabrication of unconventional computing (UC) devices is steadily transcending the barriers between science fiction and reality, but efforts in this direction are impeded by ethical considerations, the field’s restrictively broad multidisciplinarity and our incomplete knowledge of fundamental biological processes. As such, very few functional prototypes of biological UC devices have been produced to date. This thesis aims to demonstrate the computational polymorphism and polyfunctionality of a chosen biological substrate — slime mould Physarum polycephalum, an arguably ‘simple’ single-celled organism — and how these properties can be harnessed to create laboratory experimental prototypes of functionally-useful biological UC prototypes. Computing devices utilising live slime mould as their key constituent element can be developed into a) heterotic, or hybrid devices, which are based on electrical recognition of slime mould behaviour via machine-organism interfaces, b) whole-organism-scale morphological processors, whose output is the organism’s morphological adaptation to environmental stimuli (input) and c) intracellular processors wherein data are represented by energetic signalling events mediated by the cytoskeleton, a nano-scale protein network. It is demonstrated that each category of device is capable of implementing logic and furthermore, specific applications for each class may be engineered, such as image processing applications for morphological processors and biosensors in the case of heterotic devices. The results presented are supported by a range of computer modelling experiments using cellular automata and multi-agent modelling. We conclude that P. polycephalum is a polymorphic UC substrate insofar as it can process multimodal sensory input and polyfunctional in its demonstrable ability to undertake a variety of computing problems. Furthermore, our results are highly applicable to the study of other living UC substrates and will inform future work in UC, biosensing, and biomedicine