A brainstem-like modulation approach for gait transition in a quadruped robot

The ability to traverse a wide variety of terrains while walking is basically a requirement for performing useful tasks in our human centric world. In this article, we propose a bio-inspired robotic controller able to generate locomotion and to easily switch between different type of gaits. In order to improve the robot stability and response while locomoting, we adjust both the duty factor and the interlimb phase relationships, according to the velocities. We extend previous work, by applying nonlinear oscillators to generate the rhythmic locomotor movements for a quadruped robot, similarly to the biological counterparts. The generated trajectories are modulated by a drive signal, that modifies the oscillator frequency, amplitude and the coupling parameters among the oscillators, proportionally to the drive signal strength. By increasing the drive signal, locomotion can be elicited and velocity increased while switching to the appropriate gaits. This drive signal can be specified according to sensory information or set a priori. The implementation of the central pattern generator network and the activity modulation layer is shown in simulation and in an AIBO robot

Gait transition and modulation in a quadruped robot : a brainstem-like modulation approach

In this article, we propose a bio-inspired architecture for a quadruped robot that is able to initiate/stop locomotion; generate different gaits, and to easily select and switch between the different gaits according to the speed and/or the behavioral context. This improves the robot stability and smoothness while locomoting. We apply nonlinear oscillators to model Central Pattern Generators (CPGs). These generate the rhythmic locomotor movements for a quadruped robot. The generated trajectories are modulated by a tonic signal, that encodes the required activity and/or modulation. This drive signal strength is mapped onto sets of CPG parameters. By increasing the drive signal, locomotion can be elicited and velocity increased while switching to the appropriate gaits. This drive signal can be specified according to sensory information or set a priori. The system is implemented in a simulated and real AIBO robot. Results demonstrate the adequacy of the architecture to generate and modulate the required coordinated trajectories according to a velocity increase; and to smoothly and easily switch among the different motor behaviors.The authors gratefully acknowledge Keir Pearson for all the discussions and help. This work is funded by FEDER Funding supported by the Operational Program Competitive Factors COMPETE and National Funding supported by the FCT - Foundation for Science and Technology through project PTDC/EEACRO/100655/2008

Quadruped robot locomotion using a global optimization stochastic algorithm

The problem of tuning nonlinear dynamical systems parameters, such that the attained results are considered good ones, is a relevant one. This article describes the development of a gait optimization system that allows a fast but stable robot quadruped crawl gait. We combine bio-inspired Central Patterns Generators (CPGs) and Genetic Algorithms (GA). CPGs are modelled as autonomous differential equations, that generate the necessar y limb movement to perform the required walking gait. The GA finds parameterizations of the CPGs parameters which attain good gaits in terms of speed, vibration and stability. Moreover, two constraint handling techniques based on tournament selection and repairing mechanism are embedded in the GA to solve the proposed constrained optimization problem and make the search more efficient. The experimental results, performed on a simulated Aibo robot, demonstrate that our approach allows low vibration with a high velocity and wide stability margin for a quadruped slow crawl gait.This work is funded by FEDER Funding supported by the Operational Program Competitive Factors .U COMPETE and National Funding supported by the FCT Portuguese Science Foundation through project PTDC/EEACRO/100655/200

Locomotion gait optimization for a quadruped robot

This article describes the development of a gait optimization system that allows a fast but stable robot quadruped crawl gait. We focus in the development of a quadruped robot walking gait locomotion that combine bio-inspired Central Patterns Generators (CPGs) and Genetic Algorithms (GA). The CPGs are modelled as autonomous differential equations, that generate the necessary limb movement to perform the walking gait, and the Genetic Algorithm perform the search of the CPGs parameters. This approach allows to explicitly specify parameters such as amplitude, offset and frequency of movement and to smoothly modulate the generated trajectories according to changes in these parameters. It is therefore easy to combine the CPG with an optimization method. A genetic algorithm determines the best set of parameters that generates the limbs movements. We intend to obtain a walking gait locomotion that minimizes the vibration and maximizes the wide stability margin and the forward velocity. The experimental results, performed on a simulated Aibo robot, demonstrated that our approach allows low vibration with a high velocity and wide stability margin for a quadruped walking gait locomotion

A novel approach to gait synchronization and transition for reconfigurable walking platforms

Legged robots based on one degree-of-freedom reconfigurable planar leg mechanisms, that are capable of generating multiple useful gaits, are highly desired due to the possibility of handling environments and tasks of high complexity while maintaining simple control schemes. An essential consideration in these reconfigurable legged robots is to attain stability in motion, at rest as well as while transforming from one configuration to another with the minimum number of legs as long as the full range of their walking patterns, resulting from the different gait cycles of their legs, is achieved. To this end, in this paper, we present a method for the generation of input joint trajectories to properly synchronize the movement of quadruped robots with reconfigurable legs. The approach is exemplified in a four-legged robot with reconfigurable Jansen legs capable of generating up to six useful different gait cycles. The proposed technique is validated through simulated results that show the platform׳s stability across its six feasible walking patterns and during gait transition phases, thus considerably extending the capabilities of the non-reconfigurable design

Omnidirectional locomotion in a quadruped robot : a CPG-based approach

Quadruped locomotion on rough terrain and un- predictable environments is still a challenge, where the concept of Central Pattern Generators (CPG) has brought interesting ideas. In this contribution we present a CPG design based on coupled oscillators, generating the required stepping movements of a limb for omnidirectional motion. Movements are on- line modulated through small value changes in the CPG’s parameters as required to perform the desired omnidirectional locomotion in a quadruped robot. We also present a method- ology to modulate the CPG’s parameters, reducing the control dimensionality, described in terms of the robot’s translational speed, angular velocity and walking orientation. Results show the proposed controller is well suited for the online generation and modulation of the motor patterns required to achieve the desired omnidirectional walking motion

Multi-objective parameter CPG optimization for gait generation of a quadruped robot considering behavioral diversity

This paper presents a gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm. CPGs are modeled as autonomous differential equations, that generate the necessary limb movement to perform the required walking gait. In order to optimize the walking gait, four conflicting objectives are considered, simultaneously: minimize the body vibration, maximize the velocity, maximize the wide stability margin and maximize the behavioral diversity. The results of NSGA-II for this multi-objective problem are discussed. The effect of the inclusion of a behavioral diversity objective in the system is also studied in terms of the walking gait achieved. The experimental results show the effectiveness of this multi-objective approach. The several walking gait solutions obtained correspond to different trade-off between the objectives.This work is funded by FEDER Funding supported by the Operational Program Competitive Factors - COMPETE and National Funding supported by the FCT - Portuguese Science Foundation through project PTDC/EEACRO/ 100655/2008. Thanks to Dr. St ? ephane Doncieux from the Institut des Systmes Intelligents et de Robotique (ISIR) of the Pierre and Marie Curie University (UPMC

Neural Control of Interlimb Coordination and Gait Timing in Bipeds and Quadrupeds

1) A large body of behavioral data conceming animal and human gaits and gait transitions is simulated as emergent properties of a central pattern generator (CPG) model. The CPG model incorporates neurons obeying Hodgkin-Huxley type dynamics that interact via an on-center off-surround anatomy whose excitatory signals operate on a faster time scale than their inhibitory signals. A descending cornmand or arousal signal called a GO signal activates the gaits and controL their transitions. The GO signal and the CPG model are compared with neural data from globus pallidus and spinal cord, among other brain structures. 2) Data from human bimanual finger coordination tasks are simulated in which anti-phase oscillations at low frequencies spontaneously switch to in-phase oscillations at high frequencies, in-phase oscillations can be performed both at low and high frequencies, phase fluctuations occur at the anti-phase in-phase transition, and a "seagull effect" of larger errors occurs at intermediate phases. When driven by environmental patterns with intermediate phase relationships, the model's output exhibits a tendency to slip toward purely in-phase and anti-phase relationships as observed in humans subjects. 3) Quadruped vertebrate gaits, including the amble, the walk, all three pairwise gaits (trot, pace, and gallop) and the pronk are simulated. Rapid gait transitions are simulated in the order--walk, trot, pace, and gallop--that occurs in the cat, along with the observed increase in oscillation frequency. 4) Precise control of quadruped gait switching is achieved in the model by using GO-dependent modulation of the model's inhibitory interactions. This generates a different functional connectivity in a single CPG at different arousal levels. Such task-specific modulation of functional connectivity in neural pattern generators has been experimentally reported in invertebrates. Phase-dependent modulation of reflex gain has been observed in cats. A role for state-dependent modulation is herein predicted to occur in vertebrates for precise control of phase transitions from one gait to another. 5) The primary human gaits (the walk and the run) and elephant gaits (the amble and the walk) are sirnulated. Although these two gaits are qualitatively different, they both have the same limb order and may exhibit oscillation frequencies that overlap. The CPG model simulates the walk and the run by generating oscillations which exhibit the same phase relationships. but qualitatively different waveform shapes, at different GO signal levels. The fraction of each cycle that activity is above threshold quantitatively distinguishes the two gaits, much as the duty cycles of the feet are longer in the walk than in the run. 6) A key model properly concerns the ability of a single model CPG, that obeys a fixed set of opponent processing equations to generate both in-phase and anti-phase oscillations at different arousal levels. Phase transitions from either in-phase to anti-phase oscillations, or from anti-phase to in-phase oscillations, can occur in different parameter ranges, as the GO signal increases.Air Force Office of Scientific Research (90-0128, F49620-92-J-0225, 90-0175); National Science Foundation (IRI-90-24877); Office of Naval Research (N00014-92-J-1309); Army Research Office (DAAL03-88-K-0088); Advanced Research Projects Agency (90-0083

Impact of discrete corrections in a modular approach for trajectory generation in quadruped robots

Online generation of trajectories in robots is a very complex task that involves the combination of different types of movements, i.e., distinct motor primitives. The later are used to model complex behaviors in robots, such as locomotion in irregular terrain and obstacle avoidance. In this paper, we consider two motor primitives: rhythmic and discrete. We study the effect on the robots’ gaits of superimposing the two motor primitives, considering two distinct types of coupling. Additionally, we simulate two scenarios, where the discrete primitive is inserted in all of the four limbs, or is inserted in ipsilateral pairs of limbs. Numerical results show that amplitude and frequency of the periodic solutions, corresponding to the gaits trot and pace, are almost constant for diffusive and synaptic couplings.CP was supported by Research funded by the European Regional Development Fund through the programme COMPETE and by the Portuguese Government through the FCT Fundacao para a Ciencia e a Tecnologia under the project PEst-C/MAT/UI0144/2011. This work was also funded by FEDER Funding supported by the Operational Program Competitive Factors COMPETE and National Funding supported by the FCT - Portuguese Science Foundation through project PTDC/EEACRO/100655/2008