Lutz Winkler

Symbiotic robot organisms: REPLICATOR and SYMBRION projects

Cooperation and competition among stand - alone swarm agents can increase the collective fitness of the whole system. An interesting form of collective system is demonstrated by some bacteria and fungi, which can build symbiotic organisms. Symbiotic communities can enable new functional capabilities which allow all members to survive better in their environment. In this article we show an overview of two large European projects dealing with new collective robotic systems which utilize principles derived from natural symbiosis. The paper provides also an overview of typical hardware, software and methodological challenges arose along these projects, as well as some prototypes and on-going experiments available on this stage.

The Collective Self-reconfigurable Modular Organism (CoSMO)

In this paper we will present the CoSMO platform, a new mobile modular self-reconfigurable robot (MSR) platform which we developed within the two European projects REPLICATOR and SYMBRION. Compared to other MSR platforms, this platform possesses huge computational capabilities and it exhibits a large communication bandwidth between connected modules. Furthermore, its modules have the ability to share energy among each other and locomote in every main direction by their own. Due to the mechanical design, different organism topologies and motion behaviors enable CoSMO to be flexible to different tasks and to adapt to unforeseen changes in the environment. Nevertheless, the size and the mass of the robot modules are still comparable to other platforms. In this paper, we will give an overview of the architecture of the CoSMO platform, which is in its final stage of development. In particular, we will describe the mechanical, the electronic and the software design. We will present first tests with the prototype of the robot and will show the potential functionality of the platform in simulation.

High-level motion planning for CPG-driven modular robots

Modular robots may become candidates for search and rescue operations or even for future space missions, as they can change their structure to adapt to terrain conditions and to better fulfill a given task. A core problem in such missions is the ability to visit distant places in rough terrain. Traditionally, the motion of modular robots is modeled using locomotion generators that can provide various gaits, e.g. crawling or walking. However, pure locomotion generation cannot ensure that desired places in a complex environment with obstacles will in fact be reached. These cases require several locomotion generators providing motion primitives that are switched using a planning process that takes the obstacles into account. In this paper, we present a novel motion planning method for modular robots equipped with elementary motion primitives. The utilization of primitives significantly reduces the complexity of the motion planning which enables plans to be created for robots of arbitrary shapes. The primitives used here do not need to cope with environmental changes, which can therefore be realized using simple locomotion generators that are scalable, i.e., the primitives can provide motion for robots with many modules. As the motion primitives are realized using locomotion generators, no reconfiguration is required and the proposed approach can thus be used even for modular robots without self-reconfiguration capabilities. The performance of the proposed algorithm has been experimentally verified in various environments, in physical simulations and also in hardware experiments. A novel method for motion planning of modular robots is presented.The robots are equipped with a vocabulary of motion primitives.The primitives are realized using Central Pattern Generators.The motion planner combines the primitives to achieve a goal.The system is experimentally verified in simulated and real environments.

Robot3D — A simulator for mobile modular self-reconfigurable robots

A heterogeneous, mobile, self-reconfigurable and modular robot platform is being developed in the projects SYMBRION and REPLICATOR. The locomotion of the robots as well as forming of the robot organisms will be controlled using evolutionary and bio-inspired techniques. As the robots are not available at the beginning of the projects and experiments are time consuming and carry risks of damaging the robots, the evolutionary algorithms will be run using a simulation. The simulation has to provide realistic movements of a swarm of robots, simulating the docking procedure between the robots as well as simulating organism motion. High requirements are imposed on such a simulator. We developed the Robot3D simulator, which dynamically simulates a swarm of mobile robots as well as robot organisms. In this paper we will give an overview of the simulation framework, we will show first results of performance tests and we will present applications for which Robot3D has already been used.

Major Feedback Loops Supporting Artificial Evolution in Multi-modular Robotics

In multi-modular reconfigurable robotics it is extremely challenging to develop control software that is able to generate robust but still flexible behavior of the ‘robotic organism’ that is formed by several independent robotic modules. We propose artificial evolution and self-organization as methodologies to develop such control software. In this article, we present our concept to evolve a self-organized multi-modular robot. We decompose the network of feedbacks, that affect the evolutionary pathway and show why and how specific sub-components, which are involved in these feedbacks, should be subject of evolutionary adaptation. Self-organization is a major component of our framework and is implemented by a hormone-inspired controller governing the behavior of singular autonomous modules. We show first results, which were obtained by artificial evolution with our framework, and give an outlook of how the framework will be applied in future research.

The Robot Formation Language — A formal description of formations for collective robots

In this paper we will present the Robot Formation Language (RFL), a topology description language for the formation of multi robot systems, such as robot swarms or self-reconfigurable modular robot platforms. The RFL supports homogeneous as well as heterogeneous multi robot platforms. This is important especially for modular robots (we also call them robot organisms), as there can also be robots included which have a different kinematic behaviour. Additionally, it supports tools, such as active wheels, grippers or structural elements, which enhance the capabilities of a modular robot platform. As we focus on creating organisms out of a robot swarm (i.e. the swarm robots have capabilities to connect to each other to build a modular robot organism), it is important to have a common language, which describes the swarm as well as the organism. Using the RFL, we will define a distance between two formations and describe how the calculation for this purpose can be distributed among the members of the collective. RFL cannot only be used to describe the formation of a multi robot system, but it can also be used to retrieve the kinematic chain of an organism or as a genome to evolve different organism shapes for example. It is also useful for the swarm robots to identify their position in the swarm.

A distance and diversity measure for improving the evolutionary process of modular robot organisms

In this paper, we present a novel diversity measure for a population of modular robot organisms. Evaluating this diversity we will get a prospect of the fitness of future generations of organisms in an evolutionary process. The degree of the diversity in a population is a measure for the adaptability to the environment. If the diversity is too low, it is necessary to change evolutionary parameters such as mutation probabilities or to start a new evolutionary run in order to get better adapted organisms. The novel measure helps to improve and speed-up the evolutionary process, which is mandatory as the evolution of robot organisms, specially the coevolution of controller and topology of organisms is a very tedious process. In four different experiments using the Robot3D simulator and the Symbricator modular robots, we will show the usefulness of this diversity measure. The goal of the first two experiments will be the evaluation of two different selection strategies: fitness proportionate and rank selection. In the last two experiments we will explore the differences between a restrained evolution, where the type of agent, which controls an element in an organism is predetermined by its parent element, and a free evolution.

Fast on-board motion planning for modular robots

Modular robots, which are systems made of many robotic modules, can utilize various types of locomotion. Different approaches can be used to generate these basic motion skills - motion primitives. To move in a complex environment, several motion primitives are needed and a mechanism to switch them is required. This can be realized using a high-level motion planning. To enable autonomous operation of modular robots equipped with limited computational resources, it is necessary to generate the motion plans on-board, i.e., without external computers. In this paper, we propose a novel simplified motion model of a modular robot, which allows the robot to employ the motion planner as a fast on-board replanner. The proposed approach has been verified both in simulations as well as with real robots.

An alternative locomotion unit for mobile modular self-reconfigurable robots based on archimedes screws

In this paper, we introduce a new locomotion unit for mobile modular self-reconfigurable robots. The design is based on Archimedes screws and allows a robot to utilize its full potential. With this newly designed drive unit called screw drive, a robot is able to drive in almost every direction while still using a simple, easy to control setup which requires very little space. Next to a general design description, we introduce the locomotion model for the screw drive used in simulation as well as in locomotion control of the robot. Additionally, we show several experiments to confirm the versatility of the screw drive.

Automated planning as a new approach for the self-reconfiguration of mobile modular robots

We present a new approach to the solution of the self-reconfiguration problem for mobile modular robots (MMRs). The solution describes self-reconfiguration as a planning problem that can be tackled by an automated planner. In addition to the usage of the advanced domain-independent search heuristics within the planner, we introduce domain-specific heuristics into the domain description on a higher conceptual level. An explicit optimality measure is part of the given domain description. The planner can cope with difficult self-reconfigurations, e.g. involving building helper organisms. The abstract symbolic plan is executed by a behavior based robot controller, where each robot is seen as an agent that has access to local information only. The position which a robot takes in the final configuration is determined by swarm mechanisms during runtime. A coordination instance broadly monitors the self-reconfiguration. The feasibility and advantages of this approach compared to previous work on self-reconfiguration of MMRs is shown by planning and executing self-reconfiguration in simulation for several organism families with different reconfiguration complexities.