Autonomous Task-Based Evolutionary Design of Modular Robots

In an attempt to solve the problem of finding a set of multiple unique modular robotic designs that can be constructed using a given repertoire of modules to perform a specific task, a novel synthesis framework is introduced based on design optimization concepts and evolutionary algorithms to search for the optimal design. Designing modular robotic systems faces two main challenges: the lack of basic rules of thumb and design bias introduced by human designers. The space of possible designs cannot be easily grasped by human designers especially for new tasks or tasks that are not fully understood by designers. Therefore, evolutionary computation is employed to design modular robots autonomously. Evolutionary algorithms can efficiently handle problems with discrete search spaces and solutions of variable sizes as these algorithms offer feasible robustness to local minima in the search space; and they can be parallelized easily to reducing system runtime. Moreover, they do not have to make assumptions about the solution form. This dissertation proposes a novel autonomous system for task-based modular robotic design based on evolutionary algorithms to search for the optimal design. The introduced system offers a flexible synthesis algorithm that can accommodate to different task-based design needs and can be applied to different modular shapes to produce homogenous modular robots. The proposed system uses a new representation for modular robotic assembly configuration based on graph theory and Assembly Incidence Matrix (AIM), in order to enable efficient and extendible task-based design of modular robots that can take input modules of different geometries and Degrees Of Freedom (DOFs). Robotic simulation is a powerful tool for saving time and money when designing robots as it provides an accurate method of assessing robotic adequacy to accomplish a specific task. Furthermore, it is difficult to predict robotic performance without simulation. Thus, simulation is used in this research to evaluate the robotic designs by measuring the fitness of the evolved robots, while incorporating the environmental features and robotic hardware constraints. Results are illustrated for a number of benchmark problems. The results presented a significant advance in robotic design automation state of the art

Challenging the evolutionary strategy for synthesis of analogue computational circuits

There are very few reports in the past on applications of Evolutionary Strategy (ES) towards the synthesis of analogue circuits. Moreover, even fewer reports are on the synthesis of computational circuits. Last fact is mainly due to the dif-ficulty in designing of the complex nonlinear functions that these circuits perform. In this paper, the evolving power of the ES is challenged to design four computational circuits: cube root, cubing, square root and squaring functions. The synthesis succeeded due to the usage of oscillating length genotype strategy and the substructure reuse. The approach is characterized by its simplicity and represents one of the first attempts of application of ES towards the synthesis of “QR” circuits. The obtained experimental results significantly exceed the results published before in terms of the circuit quality, economy in components and computing resources utilized, revealing the great potential of the technique pro-posed to design large scale analog circuits

Self-Reconfiguration Planning in Modular Reconfigurable Robots

MSRs are highly versatile robots that work together to form into different configurations. However, to take advantage of this ability to transform, the MSR must utilize an SRP algorithm to determine what actions to perform to shape itself to reach its goal configuration. An SRP algorithm can be boiled down to a search method through an unexplored graph which we approach with four basic search algorithms to see which algorithm is best when designing an SRP algorithm. To do this we create a general MSR model known as stickbots and use different search algorithms on a variety of SRP problems to test the model. With these tests we can observe how different algorithms are affected by different scenarios. With the data collected using this model we hope to show that certain algorithms are better suited for creating SRP algorithms and our model can be used to test more complex algorithms

3D reconfiguration using graph grammars for modular robotics

The objective of this thesis is to develop a method for the reconfiguration of three-dimensional modular robots. A modular robot is composed of simple individual building blocks or modules. Each of these modules needs to be controlled and actuated individually in order to make the robot perform useful tasks. The presented method allows us to reconfigure arbitrary initial configurations of modules into any pre-specified target configuration by using graph grammar rules that rely on local information only. Local in a sense that each module needs just information from neighboring modules in order to decide its next reconfiguration step. The advantage of this approach is that the modules do not need global knowledge about the whole configuration. We propose a two stage reconfiguration process composed of a centralized planning stage and a decentralized, rule-based reconfiguration stage. In the first stage, paths are planned for each module and then rewritten into a ruleset, also called a graph grammar. Global knowledge about the configuration is available to the planner. In stage two, these rules are applied in a decentralized fashion by each node individually and with local knowledge only. Each module can check the ruleset for applicable rules in parallel. This approach has been implemented in Matlab and currently, we are able to generate rulesets for arbitrary homogeneous input configurations.MSCommittee Chair: Magnus Egerstedt; Committee Member: Jeff Shamma; Committee Member: Patricio Antonio Vel

Enabling New Functionally Embedded Mechanical Systems Via Cutting, Folding, and 3D Printing

Traditional design tools and fabrication methods implicitly prevent mechanical engineers from encapsulating full functionalities such as mobility, transformation, sensing and actuation in the early design concept prototyping stage. Therefore, designers are forced to design, fabricate and assemble individual parts similar to conventional manufacturing, and iteratively create additional functionalities. This results in relatively high design iteration times and complex assembly strategies

An autonomous self-reconfigurable modular robotic system with optimised docking connectors

Includes bibliographical references.Self-Reconfigurable Modular Robots are robotic systems consisting of a number of self-contained modules that can autonomously interconnect in different positions and orientations thereby varying the shape and size of the overall modular robot. This ground breaking capability is what in theory, makes self-reconfigurable modular robots more suitable for use in the navigation of unknown or unstructured environments. Here, they are required to reconfigure into different forms so as to optimise their navigation capabilities, a feat that is rendered impossible in conventional specialised robots that lack reconfiguration capabilities. However, the frequent development and use of self-reconfigurable modular robots in everyday robotic navigation applications is significantly hampered by the increased difficulty and overall cost of production of constituent robotic modules. One major contributor to this is the difficulty of designing suitably robust and reliable docking mechanisms between individual robotic modules. Such mechanisms are required to be mechanically stable involving a robust coupling mechanism, and to facilitate reliable inter-module power sharing and communication. This dissertation therefore proposes that the design and development of a functional low cost self-reconfigurable modular robot is indeed achievable by optimising and simplifying the design of a robust and reliable autonomous docking mechanism. In this study, we design and develop such a modular robot, whose constituent robotic modules are fitted with specialised docking connectors that utilise an optimised docking mechanism. This modular robot, its robotic modules and their connectors are then thoroughly tested for accuracy in mobility, electrical and structural stability, inter-module communication and power transfer, self-assembly, self-reconfiguration and self-healing, among others. The outcome of these testing procedures proved that it is indeed possible to optimise the docking mechanisms of self-reconfigurable modular robots, thereby enabling the modular robot to more easily exhibit efficient self-reconfiguration, self-assembly and self-healing behaviours. This study however showed that the type, shape, functionality and structure of electrical contacts used within the docking connectors for inter-module signal transfer and communication play a major role in enabling efficient self-assembly, self-reconfiguration and self-healing behaviours. Smooth spring loaded metallic electrical contacts incorporated into the docking connector design are recommended. This study also highlights the importance of closed loop control in the locomotion of constituent robotic modules, especially prior to docking. The open loop controlled locomotion optimisations used in this project were not as accurate as was initially expected, making self-assembly rather inaccurate and inconsistent. It is hoped that the outcomes of this research will serve to improve the docking mechanisms of self-reconfigurable modular robots thereby improving their functionality and pave the way for future large scale use of these robots in real world applications

Soft Scalable Self-Reconfigurable Modular Cellbot

Hazardous environments such as disaster affected areas, outer space, and radiation affected areas are dangerous for humans. Autonomous systems which can navigate through these environments would reduce risk of life. The terrains in these applications are diverse and unknown, hence there is a requirement for a robot which can self-adapt its morphology and use suitable control to optimally move in the desired manner. Although there exist monolithic robots for some of these applications, such as the Curiosity rover for Mars exploration, a modular robot containing multiple simple units could increase the fault tolerance. A modular design also enables scaling up or down of the robot based on the current task, for example, scaling up by connecting multiple units to cover a wider area or scaling down to pass through a tight space.Taking bio-inspiration from cells, where – based on environmental conditions – cells come together to form different structures to carry out different tasks, a soft modular robot called Cellbot was developed which was composed of multiple units called ‘cells’. Tests were conducted to understand the cellbot movement over different frictional surfaces for different actuation functions, the number of cells connected in a line (1D), and the shapes formed by connecting cells in 2D. A simulation model was developed to test a large range of frictional values and actuation functions for different friction coefficients. Based on the obtained results, cells could be designed using a material with frictional properties lying in the optimal locomotion range. In other cases, where the application has diverse terrains, the number of connected units can be changed to optimise the robot locomotion. Initial tests were conducted using a ‘ball robot’, where the cellbot was designed using balls which touch ground to exploit friction and actuators to provide force to move the robot. The model was extended to develop, a ‘bellow robot’ which was fabricated using hyper-elastic bellows and employed pneumatic actuation. The amount of inflation of a cell and its neighbouring cells determined if the cell would touch the ground or be lifted up. This was used to change cell behaviour where a cell could be touching ground to provide anchoring friction, or lifted to push or pull the cells and thereby move the robot. The cells were connected by magnets which could be disconnected and reconnected by morphing the robot body. The cellbot can thus reconfigure by changing the number of connected units or its shape. The easy detachment can be used to remove and replace damaged cells. Complex cellbot movements can be achieved by either switching between different robot morphologies or by changing actuation control.Future cellbots will be controlled remotely to change their morphology, control, and number of connected cells, making them suitable for missions which require fault tolerance and autonomous shape adaptation. The proposed cellbot platform has the potential to reduce the energy, time and costs in comparison to traditional robots and has potential for applications such as exploration missions for outer space, search and rescue missions for disaster affected areas, internal medical procedures, and nuclear decommissioning.<br/