Controlling swimming and crawling in a fish robot using a central pattern generator

Online trajectory generation for robots with multiple degrees of freedom is still a difficult and unsolved problem, in particular for non-steady state locomotion, that is, when the robot has to move in a complex environment with continuous variations of the speed, direction, and type of locomotor behavior. In this article we address the problem of controlling the non-steady state swimming and crawling of a novel fish robot. For this, we have designed a control architecture based on a central pattern generator (CPG) implemented as a system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters. To test our controller, we designed BoxyBot, a simple fish robot with three actuated fins capable of swimming in water and crawling on firm ground. Using the CPG model, the robot is capable of performing and switching between a variety of different locomotor behaviors such as swimming forwards, swimming backwards, turning, rolling, moving upwards/downwards, and crawling. These behaviors are triggered and modulated by sensory input provided by light, water, and touch sensors. Results are presented demonstrating the agility of the robot and interesting properties of a CPG-based control approach such as stability of the rhythmic patterns due to limit cycle behavior, and the production of smooth trajectories despite abrupt changes of control parameters. The robot is currently used in a temporary 20-month long exhibition at the EPFL. We present the hardware setup that was designed for the exhibition, and the type of interactions with the control system that allow visitors to influence the behavior of the robot. The exhibition is useful to test the robustness of the robot for long term use, and to demonstrate the suitability of the CPG-based approach for interactive control with a human in the loop. This article is an extended version of an article presented at BioRob2006 the first IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics.

Learning to move in modular robots using central pattern generators and online optimization

Auke Ijspeert, Jérôme Maye

This article addresses the problem of how modular robotics systems, i.e. systems composed of multiple modules that can be configured into different robotic structures, can learn to locomote. In particular, we tackle the problems of online learning, that is, learning while moving, and the problem of dealing with unknown arbitrary robotic structures. We propose a framework for learning locomotion controllers based on two components: a central pattern generator (CPG) and a gradient-free optimization algorithm: Powell’s method. The CPG is implemented as a system of coupled nonlinear oscillators in our YaMoR modular robotic system, with one oscillator per module. The nonlinear oscillators are coupled together across modules using Bluetooth communication to obtain specific gaits, i.e. synchronized patterns of oscillations among modules. Online learning is done by running the Powell optimization algorithm in parallel to the CPG model, with the speed of locomotion being the criterion to be optimized. Interesting aspects of the optimization are: it is carried out online, it does not require stopping or resetting the robots, and it is fast. We present results showing the interesting properties of this framework for a modular robotic system. In particular, our CPG model can readily be implemented in a distributed system, it is cheap computationally, it exhibits limit cycle behavior (temporary perturbations are rapidly forgotten), it produces smooth trajectories even when control parameters are abruptly changed, and it is robust against imperfect communication among modules. We also present results of learning to move with three different robot structures. Interesting locomotion modes are obtained after running the optimization for less than 60 minutes.

2008

Online trajectory generation in an amphibious snake robot using a lamprey-like central pattern generator model

Alessandro Crespi, Auke Ijspeert

This article presents a control architecture for controlling the locomotion of an amphibious snake/lamprey robot capable of swimming and serpentine locomotion. The control architecture is based on a central pattern generator (CPG) model inspired from the neural circuits controlling locomotion in the lamprey's spinal cord. The CPG model is implemented as a system of coupled nonlinear oscillators on board of the robot. The CPG generates coordinated travelling waves in real time while being interactively modulated by a human-operator. Interesting aspects of the CPG model include (1) that it exhibits limit cycle behavior (i.e. it produces stable rhythmic patterns that are robust against perturbations), (2) that the limit cycle behavior has a closed-form solution which provides explicit control over relevant characteristics such as frequency, amplitude and wavelength of the travelling waves, and (3) that the control parameters of the CPG can be continuously and interactively modulated by a human operator to offer high maneuverability. We demonstrate how the CPG allows one to easily adjust the speed and direction of locomotion both in water and on ground while ensuring that continuous and smooth setpoints; are sent to the robot's actuated joints.

IEEE2007

Shoaling with fish: using miniature robotic agents to close the interaction loop with groups of zebrafish Danio rerio

Frank Bonnet

Robotic animals are nowadays developed for various types of research, such as bio-inspired robotics, biomimetics and animal behavior studies. The miniaturization of technologies and the increase in performance of embedded systems allowed engineers to develop more powerful, sophisticated and miniature devices. The case of robotic fish is a typical example of such challenging design: the fish locomotion and body movements are difficult to reproduce and the device has to move autonomously underwater. More specifically, in the case of collective animal behavior research, the robotic device has to interact with animals by generating and exploiting signals relevant for social behavior. Once perceived by the animal society as conspecific, these robots can become powerful tools to study the animal behaviors, as they can at the same time monitor the changes in behavior and influence the collective choices of the animal society. In this work, we present novel robotized tools that can integrate shoals of fish in order to study their collective behaviors. This robotic platform is composed of two subsystems: a miniature wheeled mobile robot that can achieve dynamic movements and multi-robot long-duration experiments, and a robotic fish lure that is able to beat its tail to generate fish-like body movements. The two subsystems are coupled with magnets which allows the wheeled mobile robot to steer the robotic fish lure so that it reaches very high speeds and accelerations while achieving shoaling. An experimental setup to conduct studies on mixed societies of artificial and living fish was designed to facilitate the experiments for biologists. A software framework was also implemented to control the robots in a closed-loop using data extracted from visual tracking that retrieved the position of the robots and the fish. We selected the zebrafish Danio rerio as a model to perform experiments to qualify our system. We used the current state of the art on the zebrafish social behavior to define the specifications of the robots, and we performed stimuli analysis to improve their developments. Bio-inspired controllers were designed based on data extracted from experiments with zebrafish for the robots to mimic the zebrafish locomotion underwater. Experiments involving a robot with a shoal of fish in a constrained environment showed that the locomotion of the robot was one of the main factor to affect the collective behavior of zebrafish. We also shown that the body movements and the biomimetic appearance of the lure could increase its acceptance by fish. Finally, an experiment involving a mixed society of fish and robots qualified the robotic system to be integrated among a zebrafish shoal and to be able to influence the collective decisions of the fish. These results are very promising for the field of fish-robot interaction studies, as we showed the effect of the robots in long-duration experiments and repetitively, with the same order of response from the animals.

EPFL2017

Shoaling with fish: using miniature robotic agents to close the interaction loop with groups of zebrafish Danio rerio

Frank Bonnet

EPFL2017