Prescription of rhythmic patterns for legged locomotion

As the engine behind many life phenomena, motor information generated by the central nervous system (CNS) plays a critical role in the activities of all animals. In this work, a novel, macroscopic and model-independent approach is presented for creating different patterns of coupled neural oscillations observed in biological central pattern generators (CPG) during the control of legged locomotion. Based on a simple distributed state machine, which consists of two nodes sharing pre-defined number of resources, the concept of oscillatory building blocks (OBBs) is summarised for the production of elaborated rhythmic patterns. Various types of OBBs can be designed to construct a motion joint of one degree-of-freedom (DOF) with adjustable oscillatory frequencies and duty cycles. An OBBs network can thus be potentially built to generate a full range of locomotion patterns of a legged animal with controlled transitions between different rhythmic patterns. It is shown that gait pattern transition can be achieved by simply changing a single parameter of an OBB module. Essentially this simple mechanism allows for the consolidation of a methodology for the construction of artificial CPG architectures behaving as an asymmetric Hopfield neural network. Moreover, the proposed CPG model introduced here is amenable to analogue and/or digital circuit integration

Adaptive Natural Oscillator to Exploit Natural Dynamics for Energy Efficiency

We present a novel adaptive oscillator, called Adaptive Natural Oscillator (ANO), to exploit the natural dynamics of a given robotic system. This tool is built upon the Adaptive Frequency Oscillator (AFO), and it can be used as a pattern generator in robotic applications such as locomotion systems. In contrast to AFO, that adapts to the frequency of an external signal, ANO adapts the frequency of reference trajectory to the natural dynamics of the given system. In this work, we prove that, in linear systems, ANO converges to the system's natural frequency. Furthermore, we show that this tool exploits the natural dynamics for energy efficiency through minimization of actuator effort. This property makes ANO an appealing tool for energy consumption reduction in cyclic tasks; especially in legged systems. We also extend the proposed adaptation mechanism to high dimensional and general cases; such as n-DOF manipulators. In addition, by investigating a hopper leg in simulation, we show the efficacy of ANO in face of dynamical discontinuities; such as those inherent in legged locomotion. Furthermore, we apply ANO to a simulated compliant robotic manipulator performing a periodic task where the energy consumption is drastically reduced. Finally, the experimental results on a 1-DOF compliant joint show that our adaptive oscillator, despite all practical uncertainties and deviations from theoretical models, exploits the natural dynamics and reduces the energy consumption

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control

A multirobot platform based on autonomous surface and underwater vehicles with bio-inspired neurocontrollers for long-term oil spills monitoring

This paper describes the BUSCAMOS-Oil monitoring system, which is a robotic platform consisting of an autonomous surface vessel combined with an underwater vehicle. The system has been designed for the long-term monitoring of oil spills, including the search for the spill, and transmitting information on its location, extent, direction and speed. Both vehicles are controlled by two different types of bio-inspired neural networks: a Self-Organization Direction Mapping Network for trajectory generation and a Neural Network for Avoidance Behaviour for avoiding obstacles. The systems’ resilient capabilities are provided by bio-inspired algorithms implemented in a modular software architecture and controlled by redundant devices to give the necessary robustness to operate in the difficult conditions typically found in long-term oil-spill operations. The efficacy of the vehicles’ adaptive navigation system and long-term mission capabilities are shown in the experimental results.This work was partially supported by the BUSCAMOS Project (ref. 1003211003700) under the program DN8644 COINCIDENTE of the Spanish Defense Ministry, the “Research Programme for Groups of Scientific Excellence at Region of Murcia” of the Seneca Foundation (Agency for Science and Technology of the Region of Murcia-19895/GERM/15)”, and the Spanish Government’s cDrone (ref. TIN2013-45920-R) and ViSelTR (ref. TIN2012-39279) projects

Construcción, simulación y programación de un robot cuadrúpedo multipropósito de código abierto

En este proyecto se pretende modelar, simular y construir un robot cuadrúpedo basado en la plataforma open source Spot Micro (robot inspirado en Spot mini de Boston Dynamics). El objetivo es mediante el estudio de los distintos sistemas actualmente disponibles, desarrollar una plataforma robótica de bajo coste multipropósito, por fases de desarrollo. Se explorará el sistema actual, se corregirán los defectos y finalmente se mejorará dotándolo con la posibilidad de alcanzar cierto nivel de autonomía. Se pretende también generar un programa de gestión que permita el control de sus articulaciones y de los distintos sensores incorporados así como establecer las bases para el entrenamiento de un agente con aprendizaje por refuerzo que sirva como futuro controlador del robot vía teleoperación o control manual

A methodology to determine the functional workspace of a 6R robot using forward kinematics and geometrical methods

The work envelope of a robot does not capture the effect of tool orientation. Applications will require the tool to be at a certain orientation to perform the tasks necessary. It is therefore important to introduce a parameter that can capture the effect of orientation for multiple robots and configurations. This is called the functional work space, which is a subset of the work envelope would capture the effect of orientation. This research discusses the development of establishing an assessment tool that can predict the functional work space of a robot for a certain tool-orientation pair thus aiding in proper tool, tool path, fixture, related configuration selection and placement. Several solutions are studied and an analytical and a geometric solution is presented after a detailed study of joint dependencies, joint movements, limits, link lengths and displacements through visual, empirical and analytical approaches. The functional workspace curve for a manipulator with similar kinematic structure can be created using the geometrical solution discussed in this research. It is difficult to derive a general paradigm since different parameters such as, joint limits, angles and twist angles seem to have a different effect on the shape of the workspace. The geometrical solution employed is simple, easy to deduce and can be simulated with a commercial software package. Design decisions pertaining to configuration and reconfiguration of manipulators will benefit by employing the solution as a design/analysis tool. A case study involving an X-ray diffraction technique goniometer is presented to highlight the merits of this work