1,915 research outputs found
A Real-Time Solver For Time-Optimal Control Of Omnidirectional Robots with Bounded Acceleration
We are interested in the problem of time-optimal control of omnidirectional
robots with bounded acceleration (TOC-ORBA). While there exist approximate
solutions for such robots, and exact solutions with unbounded acceleration,
exact solvers to the TOC-ORBA problem have remained elusive until now. In this
paper, we present a real-time solver for true time-optimal control of
omnidirectional robots with bounded acceleration. We first derive the general
parameterized form of the solution to the TOC-ORBA problem by application of
Pontryagin's maximum principle. We then frame the boundary value problem of
TOC-ORBA as an optimization problem over the parametrized control space. To
overcome local minima and poor initial guesses to the optimization problem, we
introduce a two-stage optimal control solver (TSOCS): The first stage computes
an upper bound to the total time for the TOC-ORBA problem and holds the time
constant while optimizing the parameters of the trajectory to approach the
boundary value conditions. The second stage uses the parameters found by the
first stage, and relaxes the constraint on the total time to solve for the
parameters of the complete TOC-ORBA problem. We further implement TSOCS as a
closed loop controller to overcome actuation errors on real robots in
real-time. We empirically demonstrate the effectiveness of TSOCS in simulation
and on real robots, showing that 1) it runs in real time, generating solutions
in less than 0.5ms on average; 2) it generates faster trajectories compared to
an approximate solver; and 3) it is able to solve TOC-ORBA problems with
non-zero final velocities that were previously unsolvable in real-time
Multirobot heterogeneous control considering secondary objectives
Cooperative robotics has considered tasks that are executed frequently, maintaining the
shape and orientation of robotic systems when they fulfill a common objective, without taking
advantage of the redundancy that the robotic group could present. This paper presents a proposal
for controlling a group of terrestrial robots with heterogeneous characteristics, considering primary
and secondary tasks thus that the group complies with the following of a path while modifying its
shape and orientation at any time. The development of the proposal is achieved through the use
of controllers based on linear algebra, propounding a low computational cost and high scalability
algorithm. Likewise, the stability of the controller is analyzed to know the required features that have
to be met by the control constants, that is, the correct values. Finally, experimental results are shown
with di erent configurations and heterogeneous robots, where the graphics corroborate the expected
operation of the proposalThis research was funded by Corporación Ecuatoriana para el Desarrollo de la Investigación
y Academia–CEDI
Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices
Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments;
where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range
estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in
delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both
ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient
signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution,
tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on
TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate
an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally,
we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible
acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance
An Omnidirectional Aerial Platform for Multi-Robot Manipulation
The objectives of this work were the modeling, control and prototyping of a new fully-actuated
aerial platform. Commonly, the multirotor aerial platforms are under-actuated vehicles, since the
total propellers thrust can not be directed in every direction without inferring a vehicle body rotation.
The most common fully-actuated aerial platforms have tilted or tilting rotors that amplify
the aerodynamic perturbations between the propellers, reducing the efficiency and the provided
thrust. In order to overcome this limitation a novel platform, the ODQuad (OmniDirectional
Quadrotor), has been proposed, which is composed by three main parts, the platform, the mobile
and rotor frames, that are linked by means of two rotational joints, namely the roll and pitch
joints. The ODQuad is able to orient the total thrust by moving only the propellers frame by
means of the roll and pitch joints.
Kinematic and dynamic models of the proposed multirotor have been derived using the Euler-
Lagrange approach and a model-based controller has been designed. The latter is based on two
control loops: an outer loop for vehicle position control and an inner one for vehicle orientation
and roll-pitch joint control. The effectiveness of the controller has been tested by means of numerical
simulations in the MATLAB
c SimMechanics environment. In particular, tests in free motion
and in object transportation tasks have been carried out. In the transportation task simulation, a
momentum based observer is used to estimate the wrenches exchanged between the vehicle and
the transported object.
The ODQuad concept has been tested also in cooperative manipulation tasks. To this aim, a
simulation model was considered, in which multiple ODQuads perform the manipulation of a
bulky object with unknown inertial parameters which are identified in the first phase of the simulation.
In order to reduce the mechanical stresses due to the manipulation and enhance the system
robustness to the environment interactions, two admittance filters have been implemented: an external
filter on the object motion and an internal one local for each multirotor.
Finally, the prototyping process has been illustrated step by step. In particular, three CAD
models have been designed. The ODQuad.01 has been used in the simulations and in a preliminary
static analysis that investigated the torque values for a rough sizing of the roll-pitch joint
actuators. Since in the ODQuad.01 the components specifications and the related manufacturing
techniques have not been taken into account, a successive model, the ODQuad.02, has been designed.
The ODQuad.02 design can be developed with aluminum or carbon fiber profiles and 3D
printed parts, but each component must be custom manufactured. Finally, in order to shorten the
prototype development time, the ODQuad.03 has been created, which includes some components
of the off-the-shelf quadrotor Holybro X500 into a novel custom-built mechanical frame
Trajectory tracking and time delay management of 4-mecanum wheeled mobile robots (4-MWMR)
International audienceNowadays, wheeled mobile robots have a very important role in industrial applications, namely in transportation tasks thanks to their accuracy and rapidity. However, meeting obstacles while executing a mission can cause an important time delay, which is not appreciable in industry where production must be optimal. This paper deals with the time delay management, the trajectory generation and the tracking problem applied on four wheeled omnidirectional mobile robots. A strategy is proposed to minimize or compensate the time delay caused by obstacles. The approach is done by updating the reference trajectory. This update helps to track the trajectory in real time, a new control law based on the feedback linearization control theory is synthesized to track perfectly generated or updated trajectories
A group-theoretic approach to formalizing bootstrapping problems
The bootstrapping problem consists in designing agents that learn a model of themselves and the world, and utilize it to achieve useful tasks. It is different from other learning problems as the agent starts with uninterpreted observations and commands, and with minimal prior information about the world. In this paper, we give a mathematical formalization of this aspect of the problem. We argue that the vague constraint of having "no prior information" can be recast as a precise algebraic condition on the agent: that its behavior is invariant to particular classes of nuisances on the world, which we show can be well represented by actions of groups (diffeomorphisms, permutations, linear transformations) on observations and commands. We then introduce the class of bilinear gradient dynamics sensors (BGDS) as a candidate for learning generic robotic sensorimotor cascades. We show how framing the problem as rejection of group nuisances allows a compact and modular analysis of typical preprocessing stages, such as learning the topology of the sensors. We demonstrate learning and using such models on real-world range-finder and camera data from publicly available datasets
- …