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The fields of modular and origami robotics have become increasingly popular in recent years, with both approaches presenting particular benefits, as well as limitations, to the end user. Christoph Belke and Jamie Paik from RRL, EPFL and NCCR Robotics have recently proposed an elegant new solution that integrates both types of robotics in order to …
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To date, most modular robotic systems lack flexibility when increasing the number of modules due to their hard building blocks and rigid connection mechanisms. In order to improve adaptation to environmental changes, softness on the module level might be beneficial. However, coping with softness requires fundamental rethinking the way modules are built. A major challenge is to develop a connection mechanism that does not limit the softness of the modules, does not require precise alignment and allows for easy detachment. In this paper, we propose a soft active connection mechanism based on electroadhesion. The mechanism uses electrostatic forces to connect modules. The method is easy to implement and can be integrated in a wide range of soft module types. Based on our experimental results, we conclude that the mechanism is suitable as a connection principle for light-weight modules when efficiency in a wide range of softness, tolerance to alignment and easy detachment are desired. The main contributions of this article are (i) the qualitative comparison of different connector principles for soft modular robots, (ii) the integration of electroadhesion, featuring a novel electrode pattern design, into soft modules, and (iii) the demonstration and characterization of the performance of functional soft module mockups including the connection mechanism.
We present the hardware and reconfiguration experiments for an autonomous self-reconfigurable modular robot called Roombots (RB). RB were designed to form the basis for self-reconfigurable furniture. Each RB module contains three degrees of freedom that have been carefully selected to allow a single module to reach any position on a 2-dimensional grid and to overcome concave corners in a 3-dimensional grid. For the first time we demonstrate locomotion capabilities of single RB modules through reconfiguration with real hardware. The locomotion through reconfiguration is controlled by a planner combining the well-known D* algorithm and composed motor primitives. The novelty of our approach is the use of an online running hierarchical planner closely linked to the real hardware.
This paper proposes a new robotic platform based on origami robots and reconfigurable modular robots. The concept combines the advantages of both robot types into a mobile, quasi-two-dimensional, lattice-type reconfigurable modular origami robot, Mori. A detailed description and analysis of the concept is validated by the presentation of a first prototype that incorporates the key functionalities of the proposed system. The modular robot prototype is mobile, can be connected to other modules of its kind, and fold up to create task-specific three-dimensional reconfigurable structures. Three implementations using the prototype in different configurations are presented in form of individual modules, modular reconfigurable surfaces, and applied to closed-loop object manipulation. The experiments highlight the capabilities and advantages of the system with respect to modularity, origami-folding, mobility, and versatility.
Programmable self-assembly of chained modules holds potential for the automatic shape formation of morphologically adapted robots. However, current systems are limited to modules of uniform rigidity, which restricts the range of obtainable morphologies and thus the functionalities of the system. To address these challenges, we previously introduced soft cells as modules that can obtain different mechanical softness pre-setting. We showed that such a system can obtain a higher diversity of morphologies compared to state-of-the-art systems and we illustrated the system’s potential by demonstrating the self-assembly of complex morphologies. In this paper, we extend our previous work and present an automatic method that exploits our system’s capabilities in order to find a linear chain of soft cells that self-folds into a target 2-D shape.
This paper presents the results of a study on the effect of in-series compliance on the locomotion of a simulated 8-DoF Lola-OP Modular Snake Robot with added compliant elements. We explore whether there is an optimal stiffness for gait, terrain type, or several gaits and several terrains (i.e. a good “general-purpose” stiffness). Compliance was simulated using ball joints with eight different levels of stiffness. Two snake locomotion gaits (rolling and sidewinding) were tested over flat ground and three different types of rough terrains. We performed grid search and Particle Swarm Optimization to identify the locomotion parameters leading to fast locomotion and analyzed the best candidates in terms of locomotion speed and energy efficiency (cost of transport). Contrary to our expectations, we did not observe a clear trend that would favor the use of compliant elements over rigid structures. For sidewinding, compliant and stiff elements lead to comparable performances. For rolling gait, the general rule seems to be “the stiffer, the better”.
Modular or multi-cellular robots hold the promise to adapt their morphology to task and environment. However, research in modular robotics has traditionally been limited to mechanically non-adaptive systems due to hard building blocks and rigid connection mechanisms. To improve adaptation and global flexibility, we suggest the use of modules made of soft materials. Thanks to recent advances in fabrication techniques the development of soft robots without spatial or material constraints is now possible. In order to exploit this vast design space, computer simulations are a time and cost-efficient tool. However, there is currently no framework available that allows studying the dynamics of soft multi-cellular systems. In this work, we present our simulation framework named Soft Cell Simulator (SCS) that enables to study both mechanical design parameters as well as control problems of soft multi-cellular systems in an time-efficient yet globally accurate manner. Its main features are: (i) high simulation speed to test systems with a large number of cells (real-time up to 100 cells), (ii) large non-linear deformations without module self-penetration, (iii) tunability of module softness (0-500 N/m), (iv) physics-based module connectivity, (v) variability of module shape using internal actuators. We present results that validate the plausibility of the simulated soft cells, the scalability as well as the usability of the simulator. We suggest that this simulator helps to master and leverage the potential of the vast design space to generate novel soft multi-cellular robots.
Programmable self-assembly of chained robotic systems holds potential for the automatic construction of complex robots from a minimal set of building blocks. However, current robotic platforms are limited to modules of uniform rigidity, which results in a limited range of obtainable morphologies and thus functionalities of the system. To address these challenges, we investigate in this paper the role of softness in a programmed self-assembling chain system. We rely on a model system consisting of “soft cells” as modules that can obtain different mechanical softness presettings. Starting from a linear chain configuration, the system self-folds into a target morphology based on the intercellular interactions. We systematically investigate the influence of mechanical softness of the individual cells on the self-assembly process. Also, we test the hypothesis that a mixed distribution of cells of different softness enhances the diversity of achievable morphologies at a given resolution compared to systems with modules of uniform rigidity. Finally, we illustrate the potential of our system by the programmable self-assembly of complex and curvilinear morphologies that state-of-the-art systems can only achieve by significantly increasing their number of modules.