This paper presents the design, construction, and control for a novel concept of self-assembling robots in a system. The system is composed of multiple cooperative robots that are designed to self-assemble in a multip...
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ISBN:
(纸本)9780889865952
This paper presents the design, construction, and control for a novel concept of self-assembling robots in a system. The system is composed of multiple cooperative robots that are designed to self-assemble in a multipie-robot system, execute manipulative tasks, and self-repair, all without human assistance to achieve both autonomy and robustness. The self-assembling feature employs four mechanical design guidelines: independent module, one touch assembly design, self-alignment, and self-guiding. The independent design feature also employs independent motor control boards and wireless communication board. For a decoupling effect, we chose a motor with large gear ratio. For safety and modularization purpose, we design and implement a newly designed Series Elastic Actuator to limit shock bandwidth and sense forces during manipulative tasks. With the design and control method, we can use the modular robot without considering the arm dynamics.
In this paper, we study a heterogeneous robot team composed of self-assembling robots and aerial robots that cooperate with each other to carry out global tasks. We introduce supervised morphogenesis - an approach in ...
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ISBN:
(纸本)9781627481564
In this paper, we study a heterogeneous robot team composed of self-assembling robots and aerial robots that cooperate with each other to carry out global tasks. We introduce supervised morphogenesis - an approach in which aerial robots exploit their better view of the environment to detect tasks on the ground that require self-assembly, and perform on-board simulations to determine the morphology most adequate to carry out the task. In case existing morphologies on the ground do not match those determined in simulation, aerial robots use a series of enabling mechanisms to initiate and control (hence supervise) the formation of morphologies more adequate to carry out the task. Supervised morphogenesis solely employs LEDs and camera-based local communication between the two robot types. We validate the applicability of our approach in a real-world scenario, in which ground-based robots are given the task to cross an unknown, undulated terrain by forming ad-hoc morphologies under the supervision of an aerial robot.
A robot swarm is a solution for difficult and large scale tasks. However, controlling and coordinating a swarm of robots is challenging, because of the complexity and uncertainty of the environment where manual progra...
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ISBN:
(纸本)9783319936987;9783319936970
A robot swarm is a solution for difficult and large scale tasks. However, controlling and coordinating a swarm of robots is challenging, because of the complexity and uncertainty of the environment where manual programming of robot behaviours is often impractical. In this study we propose a hyper-heuristic methodology for swarm robots, It allows robots to create suitable actions based on a set of low-level heuristics, where each heuristic is a behavioural element. With online learning, the robot behaviours can be improved during execution by autonomous heuristic adjustment. The proposed hyper-heuristic framework is applied to surface cleaning tasks on buildings where multiple separate surfaces exist and complete surface information is difficult to obtain. Under this scenario, the robot swarm not only needs to clean the surfaces efficiently by distributing the robots, but also to move across surfaces by self-assembling into a bridge structure. Experimental results showed the effectiveness of the hyper-heuristic framework;the same group of robots was able to autonomously deal with multiple surfaces of different layouts. Their behaviours can improve over time because of the online learning mechanism.
self-assembling robots have the potential to undergo autonomous morphological adaptation. However, due to the simplicity in their hardware makeup and their limited perspective of the environment, self-assembling robot...
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self-assembling robots have the potential to undergo autonomous morphological adaptation. However, due to the simplicity in their hardware makeup and their limited perspective of the environment, self-assembling robots are often not able to reach their potential and adapt their morphologies to tasks or environments without external cues or prior information. In this paper, we present supervised morphogenesis - a control methodology that makes self-assembling robots truly flexible by enabling aerial robots to exploit their elevated position and better view of the environment to initiate and control (hence supervise) morphology formation on the ground. We present results of two case studies in which we assess the feasibility of the presented methodology using real robotic hardware. In the case studies, we implemented supervised morphogenesis using two different aerial platforms and up to six self-assembling autonomous robots. We furthermore quantify the benefits attainable for self-assembling robots through cooperation with aerial robots using simulation-based studies. The research presented in this paper is a significant step towards realizing the true potential of self-assembling robots by enabling autonomous morphological adaptation to a priori unknown tasks and environments. (C) 2018 Elsevier B.V. All rights reserved.
We examine the ability of a swarm robotic system to transport cooperatively objects of different shapes and sizes. We simulate a group of autonomous mobile robots that can physically connect to each other and to the t...
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We examine the ability of a swarm robotic system to transport cooperatively objects of different shapes and sizes. We simulate a group of autonomous mobile robots that can physically connect to each other and to the transported object. Controllers - artificial neural networks - are synthesised by an evolutionary algorithm. They are trained to let the robotsself-assemble, that is, organise into collective physical structures and transport the object towards a target location. We quantify the performance and the behaviour of the group. We show that the group can cope fairly well with objects of different geometries as well as with sudden changes in the target location. Moreover, we show that larger groups, which are made of up to 16 robots, make possible the transport of heavier objects. Finally, we discuss the limitations of the system in terms of task complexity, scalability and fault tolerance and point out potential directions for future research.
Swarm robots continue to become more prominent in solving challenging tasks in real world applications. Due to the complexity of operating in often unknown environments, centralised control of swarm robots is not idea...
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ISBN:
(纸本)9781728121536
Swarm robots continue to become more prominent in solving challenging tasks in real world applications. Due to the complexity of operating in often unknown environments, centralised control of swarm robots is not ideal. Prior manual programming is also not practical under these kind of circumstances. Thus, we establish a hyper-heuristic based learning approach for swarm robot control. With this framework, robots can autonomously identify appropriate heuristics from a set of given low-level heuristics, each heuristic guiding certain behaviours. We evaluated this type of online learning on building surface cleaning and studied the effectiveness of our hyper-heuristic online learning. Nine heuristics were proposed in this study. Through the experiments it can be seen that robots can improve their cleaning performance through the online learning process. More importantly, the experiments show that appropriate heuristics can be selected even when the size of the heuristic set is changed. The study on four types of environments shows that with the same heuristic set, the robot swarm can adapt to different environments for different tasks. Hence, hyper-heuristic learning is an effective method for decentralised control of swarm robots.
Our long-term goal of creating programmable matter will be achieved when we have the ability to build objects whose physical properties, such as shape, stiffness, optical characteristics, acoustics, or viscosity, can ...
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Our long-term goal of creating programmable matter will be achieved when we have the ability to build objects whose physical properties, such as shape, stiffness, optical characteristics, acoustics, or viscosity, can be programmed on demand. In this article, we survey the history of modular robotics and their connections to programmable matter systems capable of realizing arbitrarily shapes on demand. The goal shape may be a robot built for a specific task (a snake to pass through a tunnel or a rolling belt to quickly cover open ground) or an object designed for a particular job (such as a wrench, hammer, or bridge). When the task is complete, the modules in the structure can disconnect and be reused to create a different object. This type of self-reconfiguration leads to versatile robots that can support multiple modalities of locomotion, manipulation, and perception. Such variable architecture robots have been studied in the context of self-assembling systems, self-reconfiguring systems, self-repairing systems, and self-organizing systems.
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