314 research outputs found

    In silico case studies of compliant robots: AMARSI deliverable 3.3

    Get PDF
    In the deliverable 3.2 we presented how the morphological computing ap- proach can significantly facilitate the control strategy in several scenarios, e.g. quadruped locomotion, bipedal locomotion and reaching. In particular, the Kitty experimental platform is an example of the use of morphological computation to allow quadruped locomotion. In this deliverable we continue with the simulation studies on the application of the different morphological computation strategies to control a robotic system

    Development Of Walking Gaits For Quadruped Robot (4-Legged Robot)

    Get PDF
    The project outcomes of this project are to develop the walking gaits for the quadruped robot including trotting gait, to produce printed circuit board (PCB) for the electronic parts of the robot and to improve on the motor torque for better lifting capability and to model the gaits and implementation of the quadruped robot on ADAM software. This project is the continuation of the project completed by Mr. Yee Yuan Bin whereby he managed to develop the control system that enables the robot to perform crawling gait on the flat and horizontal surface. The control system designed involves gait control, stability control and motor control. Therefore, the existing crawling gait is to be improved into trotting gait. Besides, the modelling of the quadruped robot is to be performed using ADAMS software and the PCB for the electronic parts of the robot is to be produced in order to reduce the weight of the body. This project is split to two phases. Phase 1 is to be carried out during semester FYP 1 while Phase 2 is commenced during FYP 2. The work aspects of phase 1 are on producing printed circuit board (PCB), modelling the walking gaits using ADAMS software and also to learn about C programming for PIC18. Phase 2 is the testing stage with the presence of servomotors and circuit board as well as improvement and development of the walking gaits. At the end of project, the quadruped prototype is meant to perform forward trotting gait on flat and horizontal grounds

    Transfer learning of gaits on a quadrupedal robot

    Get PDF
    Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Learning new gaits for compliant robots is a challenging multi-dimensional optimization task. Furthermore, to ensure optimal performance, the optimization process must be repeated for every variation in the environment, for example for every change in inclination of the terrain. This is unfortunately not possible using current approaches, since the time required for the optimization is simply too high. Hence, a sub-optimal gait is often used. The goal in this manuscript is to reduce the learning time of a particle swarm algorithm, such that the robot's gaits can be optimized over a wide variety of terrains. To facilitate this, we use transfer learning by sharing knowledge about gaits between the different environments. Our findings indicate that using transfer learning new robust gaits can be discovered faster compared to traditional methods that learn a gait for each environment independently.EC/FP7/248311/EU/Adaptive Modular Architecture for Rich Motor Skills/AMARS

    Incorporating prior knowledge into deep neural network controllers of legged robots

    Get PDF

    A literature review on the optimization of legged robots

    Get PDF
    Over the last two decades the research and development of legged locomotion robots has grown steadily. Legged systems present major advantages when compared with ‘traditional’ vehicles, because they allow locomotion in inaccessible terrain to vehicles with wheels and tracks. However, the robustness of legged robots, and especially their energy consumption, among other aspects, still lag behind mechanisms that use wheels and tracks. Therefore, in the present state of development, there are several aspects that need to be improved and optimized. Keeping these ideas in mind, this paper presents the review of the literature of different methods adopted for the optimization of the structure and locomotion gaits of walking robots. Among the distinct possible strategies often used for these tasks are referred approaches such as the mimicking of biological animals, the use of evolutionary schemes to find the optimal parameters and structures, the adoption of sound mechanical design rules, and the optimization of power-based indexes

    Motion Planning for Quadrupedal Locomotion:Coupled Planning, Terrain Mapping and Whole-Body Control

    Get PDF
    Planning whole-body motions while taking into account the terrain conditions is a challenging problem for legged robots since the terrain model might produce many local minima. Our coupled planning method uses stochastic and derivatives-free search to plan both foothold locations and horizontal motions due to the local minima produced by the terrain model. It jointly optimizes body motion, step duration and foothold selection, and it models the terrain as a cost-map. Due to the novel attitude planning method, the horizontal motion plans can be applied to various terrain conditions. The attitude planner ensures the robot stability by imposing limits to the angular acceleration. Our whole-body controller tracks compliantly trunk motions while avoiding slippage, as well as kinematic and torque limits. Despite the use of a simplified model, which is restricted to flat terrain, our approach shows remarkable capability to deal with a wide range of noncoplanar terrains. The results are validated by experimental trials and comparative evaluations in a series of terrains of progressively increasing complexity

    Genetically evolved dynamic control for quadruped walking

    Get PDF
    The aim of this dissertation is to show that dynamic control of quadruped locomotion is achievable through the use of genetically evolved central pattern generators. This strategy is tested both in simulation and on a walking robot. The design of the walker has been chosen to be statically unstable, so that during motion less than three supporting feet may be in contact with the ground. The control strategy adopted is capable of propelling the artificial walker at a forward locomotion speed of ~1.5 Km/h on rugged terrain and provides for stability of motion. The learning of walking, based on simulated genetic evolution, is carried out in simulation to speed up the process and reduce the amount of damage to the hardware of the walking robot. For this reason a general-purpose fast dynamic simulator has been developed, able to efficiently compute the forward dynamics of tree-like robotic mechanisms. An optimization process to select stable walking patterns is implemented through a purposely designed genetic algorithm, which implements stochastic mutation and cross-over operators. The algorithm has been tailored to address the high cost of evaluation of the optimization function, as well as the characteristics of the parameter space chosen to represent controllers. Experiments carried out on different conditions give clear indications on the potential of the approach adopted. A proof of concept is achieved, that stable dynamic walking can be obtained through a search process which identifies attractors in the dynamics of the motor-control system of an artificial walker
    • …
    corecore