247 research outputs found
System design of a quadrupedal galloping machine
In this paper we present the system design of a machine that we have constructed to study a quadrupedal gallop gait. The gallop gait is the preferred high-speed gait of most cursorial quadrupeds. To gallop, an animal must generate ballistic trajectories with characteristic strong impacts, coordinate leg movements with asymmetric footfall phasing, and effectively use compliant members, all the while maintaining dynamic stability. In this paper we seek to further understand the primary biological features necessary for galloping by building and testing a robotic quadruped similar in size to a large goat or antelope. These features include high-speed actuation, energy storage, on-line learning control, and high-performance attitude sensing. Because body dynamics are primarily influenced by the impulses delivered by the legs, the successful design and control of single leg energetics is a major focus of this work. The leg stores energy during flight by adding tension to a spring acting across an articulated knee. During stance, the spring energy is quickly released using a novel capstan design. As a precursor to quadruped control, two intelligent strategies have been developed for verification on a one-legged system. The Levenberg-Marquardt on-line learning method is applied to a simple heuristic controller and provides good control over height and forward velocity. Direct adaptive fuzzy control, which requires no system modeling but is more computationally expensive, exhibits better response. Using these techniques we have been successful in operating one leg at speeds necessary for a dynamic gallop of a machine of this scale. Another necessary component of quadruped locomotion is high-resolution and high-bandwidth attitude sensing. The large ground impact accelerations, which cause problems for any single traditional sensor, are overcome through the use of an inertial sensing approach using updates from optical sensors and vehicle kinematics
Autonomous Locomotion Mode Transition Simulation of a Track-legged Quadruped Robot Step Negotiation
Multi-modal locomotion (e.g. terrestrial, aerial, and aquatic) is gaining
increasing interest in robotics research as it improves the robots
environmental adaptability, locomotion versatility, and operational
flexibility. Within the terrestrial multiple locomotion robots, the advantage
of hybrid robots stems from their multiple (two or more) locomotion modes,
among which robots can select from depending on the encountering terrain
conditions. However, there are many challenges in improving the autonomy of the
locomotion mode transition between their multiple locomotion modes. This work
proposed a method to realize an autonomous locomotion mode transition of a
track-legged quadruped robot steps negotiation. The autonomy of the
decision-making process was realized by the proposed criterion to comparing
energy performances of the rolling and walking locomotion modes. Two climbing
gaits were proposed to achieve smooth steps negotiation behaviours for energy
evaluation purposes. Simulations showed autonomous locomotion mode transitions
were realized for negotiations of steps with different height. The proposed
method is generic enough to be utilized to other hybrid robots after some
pre-studies of their locomotion energy performances
SWheg: A Wheel-Leg Transformable Robot With Minimalist Actuator Realization
This article presents the design, implementation, and performance evaluation
of SWheg, a novel modular wheel-leg transformable robot family with minimalist
actuator realization. SWheg takes advantage of both wheeled and legged
locomotion by seamlessly integrating them on a single platform. In contrast to
other designs that use multiple actuators, SWheg uses only one actuator to
drive the transformation of all the wheel-leg modules in sync. This means an
N-legged SWheg robot requires only N+1 actuators, which can significantly
reduce the cost and malfunction rate of the platform. The tendon-driven
wheel-leg transformation mechanism based on a four-bar linkage can perform fast
morphology transitions between wheels and legs. We validated the design
principle with two SWheg robots with four and six wheel-leg modules separately,
namely Quadrupedal SWheg and Hexapod SWheg. The design process, mechatronics
infrastructure, and the gait behavioral development of both platforms were
discussed. The performance of the robot was evaluated in various scenarios,
including driving and turning in wheeled mode, step crossing, irregular terrain
passing, and stair climbing in legged mode. The comparison between these two
platforms was also discussed
Unsupervised Contact Learning for Humanoid Estimation and Control
This work presents a method for contact state estimation using fuzzy
clustering to learn contact probability for full, six-dimensional humanoid
contacts. The data required for training is solely from proprioceptive sensors
- endeffector contact wrench sensors and inertial measurement units (IMUs) -
and the method is completely unsupervised. The resulting cluster means are used
to efficiently compute the probability of contact in each of the six
endeffector degrees of freedom (DoFs) independently. This clustering-based
contact probability estimator is validated in a kinematics-based base state
estimator in a simulation environment with realistic added sensor noise for
locomotion over rough, low-friction terrain on which the robot is subject to
foot slip and rotation. The proposed base state estimator which utilizes these
six DoF contact probability estimates is shown to perform considerably better
than that which determines kinematic contact constraints purely based on
measured normal force.Comment: Submitted to the IEEE International Conference on Robotics and
Automation (ICRA) 201
Unsupervised Contact Learning for Humanoid Estimation and Control
This work presents a method for contact state estimation using fuzzy
clustering to learn contact probability for full, six-dimensional humanoid
contacts. The data required for training is solely from proprioceptive sensors
- endeffector contact wrench sensors and inertial measurement units (IMUs) -
and the method is completely unsupervised. The resulting cluster means are used
to efficiently compute the probability of contact in each of the six
endeffector degrees of freedom (DoFs) independently. This clustering-based
contact probability estimator is validated in a kinematics-based base state
estimator in a simulation environment with realistic added sensor noise for
locomotion over rough, low-friction terrain on which the robot is subject to
foot slip and rotation. The proposed base state estimator which utilizes these
six DoF contact probability estimates is shown to perform considerably better
than that which determines kinematic contact constraints purely based on
measured normal force.Comment: Submitted to the IEEE International Conference on Robotics and
Automation (ICRA) 201
System Design of a Cheetah Robot Toward Ultra-high Speed
High-speed legged locomotion pushes the limits of the most challenging problems of design and development of the mechanism, also the control and the perception method. The cheetah is an existence proof of concept of what we imitate for high-speed running, and provides us lots of inspiration on design. In this paper, a new model of a cheetah-like robot is developed using anatomical analysis and design. Inspired by a biological neural mechanism, we propose a novel control method for controlling the muscles' flexion and extension, and simulations demonstrate good biological properties and leg's trajectory. Next, a cheetah robot prototype is designed and assembled with pneumatic muscles, a musculoskeletal structure, an antagonistic muscle arrangement and a J-type cushioning foot. Finally, experiments of the robot legs swing and kick ground tests demonstrate its natural manner and validate the design of the robot. In the future, we will test the bounding behaviour of a real legged system
Transfer learning of gaits on a quadrupedal robot
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
Thrust control, stabilization and energetics of a quadruped running robot
In order to achieve powered autonomous running robots it is essential to develop efficient actuator systems, especially for generating the radial thrust in the legs. In addition, the control of the radial thrust of the legs can be a simple, effective method for stabilizing the body pitch in a running gait. This paper presents the mechanical systems, models and control strategies employed to generate and control leg thrust in the KOLT quadruped running robot. An analytical model of the electro-pneumatic leg thrusting system is presented and analyzed to evaluate its performance and to facilitate the design of control strategies. Several experiments have been conducted to estimate the energy losses and determine their origins as well as to compute the energetic efficiency of the actuation system. Two thrust control methods are also proposed and tested experimentally. The closed loop method regulates thrust through the control of the hip liftoff speed, a conceptually simple control strategy that stabilizes the body pitch in pronk and trot gaits without the need for central feedback, even on irregular terrain. The open-loop control method regulates the energy added in each hop based on the model of the actuator system. The efficacy of these models and techniques is tested in several planar trot and pronk experiments, and the results are analyzed focusing on the body stabilization, the power consumption and the energetic efficiency. © SAGE Publications 2008 Los Angeles
Humanoid Robots
For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion
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