5,826 research outputs found
Benchmarking Cerebellar Control
Cerebellar models have long been advocated as viable models
for robot dynamics control. Building on an increasing insight
in and knowledge of the biological cerebellum, many models have been
greatly refined, of which some computational models have emerged
with useful properties with respect to robot dynamics control.
Looking at the application side, however, there is a totally different
picture. Not only is there not one robot on the market which uses
anything remotely connected with cerebellar control, but even in
research labs most testbeds for cerebellar models are restricted to
toy problems. Such applications hardly ever exceed the complexity of
a 2 DoF simulated robot arm; a task which is hardly representative for
the field of robotics, or relates to realistic applications.
In order to bring the amalgamation of the two fields forwards, we
advocate the use of a set of robotics benchmarks, on which existing
and new computational cerebellar models can be comparatively tested.
It is clear that the traditional approach to solve robotics dynamics
loses ground with the advancing complexity of robotic structures;
there is a desire for adaptive methods which can compete as traditional
control methods do for traditional robots.
In this paper we try to lay down the successes and problems in the
fields of cerebellar modelling as well as robot dynamics control.
By analyzing the common ground, a set of benchmarks is suggested
which may serve as typical robot applications for cerebellar models
A passivity based control methodology for flexible joint robots with application to a simplified shuttle RMS arm
The main goal is to develop a general theory for the control of flexible robots, including flexible joint robots, flexible link robots, rigid bodies with flexible appendages, etc. As part of the validation, the theory is applied to the control law development for a test example which consists of a three-link arm modeled after the shoulder yaw joint of the space shuttle remote manipulator system (RMS). The performance of the closed loop control system is then compared with the performance of the existing RMS controller to demonstrate the effectiveness of the proposed approach. The theoretical foundation of this new approach to the control of flexible robots is presented and its efficacy is demonstrated through simulation results on the three-link test arm
Robust tuning of robot control systems
The computed torque control problem is examined for a robot arm with flexible, geared, joint drive systems which are typical in many industrial robots. The standard computed torque algorithm is not directly applicable to this class of manipulators because of the dynamics introduced by the joint drive system. The proposed approach to computed torque control combines a computed torque algorithm with torque controller at each joint. Three such control schemes are proposed. The first scheme uses the joint torque control system currently implemented on the robot arm and a novel form of the computed torque algorithm. The other two use the standard computed torque algorithm and a novel model following torque control system based on model following techniques. Standard tasks and performance indices are used to evaluate the performance of the controllers. Both numerical simulations and experiments are used in evaluation. The study shows that all three proposed systems lead to improved tracking performance over a conventional PD controller
Control of flexible joint robotic manipulator using tuning functions design
The goal of this thesis is to design the controller for a single arm manipulator having a flexible joint for the tracking problem in two different cases. A controller is designed for a deterministic case wherein the plant parameters are assumed to be known while another is designed for an adaptive case where all the plant parameters are assumed to be unknown. In general the tracking problem is; given a smooth reference trajectory, the end effector has to track the reference while maintaining the stability. It is assumed that only the output of the manipulator, which is the link angle, is available for measurement. Also without loss of generality, the fast dynamics, that is the dynamics of the driver side of the system are neglected for the sake of simplicity; In the first case, the design procedure adopted is called observer backstepping. Since the states of the system are unavailable for measurement, an observer is designed that estimates the system states. These estimates are fed to the controller which in turn produces the control input to the system; The second case employs a design procedure called tuning functions design. In this case, since the plant parameters are unknown, the observer designed in case one cannot be used for determining the state estimates. For this purpose, parameter update laws and filters are designed for estimation of plant parameters. The filters employed are k-filters. The k-filters and the parameter update laws are given as input to the controller, which generates the control input to the system; For both cases, the mathematical models are simulated using Matlab/Simulink, and the results are verified
Bipedal Hopping: Reduced-order Model Embedding via Optimization-based Control
This paper presents the design and validation of controlling hopping on the
3D bipedal robot Cassie. A spring-mass model is identified from the kinematics
and compliance of the robot. The spring stiffness and damping are encapsulated
by the leg length, thus actuating the leg length can create and control hopping
behaviors. Trajectory optimization via direct collocation is performed on the
spring-mass model to plan jumping and landing motions. The leg length
trajectories are utilized as desired outputs to synthesize a control Lyapunov
function based quadratic program (CLF-QP). Centroidal angular momentum, taking
as an addition output in the CLF-QP, is also stabilized in the jumping phase to
prevent whole body rotation in the underactuated flight phase. The solution to
the CLF-QP is a nonlinear feedback control law that achieves dynamic jumping
behaviors on bipedal robots with compliance. The framework presented in this
paper is verified experimentally on the bipedal robot Cassie.Comment: 8 pages, 7 figures, accepted by IROS 201
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