34 research outputs found
Robust Decentralized Abstractions for Multiple Mobile Manipulators
This paper addresses the problem of decentralized abstractions for multiple
mobile manipulators with 2nd order dynamics. In particular, we propose
decentralized controllers for the navigation of each agent among predefined
regions of interest in the workspace, while guaranteeing at the same time
inter-agent collision avoidance and connectivity maintenance for a subset of
initially connected agents. In that way, the motion of the coupled multi-agent
system is abstracted into multiple finite transition systems for each agent,
which are then suitable for the application of temporal logic-based high level
plans. The proposed methodology is decentralized, since each agent uses local
information based on limited sensing capabilities. Finally, simulation studies
verify the validity of the approach.Comment: Accepted for publication in the IEEE Conference on Decision and
Control, Melbourne, Australia, 201
Optimal strategies in the average consensus problem
We prove that for a set of communicating agents to compute the average of
their initial positions (average consensus problem), the optimal topology of
communication is given by a de Bruijn's graph. Consensus is then reached in a
finitely many steps. A more general family of strategies, constructed by block
Kronecker products, is investigated and compared to Cayley strategies.Comment: 9 pages; extended preprint with proofs of a CDC 2007 (Conference on
decision and Control) pape
Robust Motion Control for Mobile Manipulator Using Resolved Acceleration and Proportional-Integral Active Force Control
A resolved acceleration control (RAC) and proportional-integral active force
control (PIAFC) is proposed as an approach for the robust motion control of a
mobile manipulator (MM) comprising a differentially driven wheeled mobile
platform with a two-link planar arm mounted on top of the platform. The study
emphasizes on the integrated kinematic and dynamic control strategy in which
the RAC is used to manipulate the kinematic component while the PIAFC is
implemented to compensate the dynamic effects including the bounded
known/unknown disturbances and uncertainties. The effectivenss and robustness
of the proposed scheme are investigated through a rigorous simulation study and
later complemented with experimental results obtained through a number of
experiments performed on a fully developed working prototype in a laboratory
environment. A number of disturbances in the form of vibratory and impact
forces are deliberately introduced into the system to evaluate the system
performances. The investigation clearly demonstrates the extreme robustness
feature of the proposed control scheme compared to other systems considered in
the study
Obstacle Avoidance in Formation Using Navigation-like Functions and Constraint Based Programming
Abstract-In this paper, we combine navigation functionlike potential fields and constraint based programming to achieve obstacle avoidance in formation. Constraint based programming was developed in robotic manipulation as a technique to take several constraints into account when controlling redundant manipulators. The approach has also been generalized, and applied to other control systems such as dual arm manipulators and unmanned aerial vehicles. Navigation functions are an elegant way to design controllers with provable properties for navigation problems. By combining these tools, we take advantage of the redundancy inherent in a multi-agent control problem and are able to concurrently address features such as formation maintenance and goal convergence, even in the presence of moving obstacles. We show how the user can decide a priority ordering of the objectives, as well as a clear way of seeing what objectives are currently addressed and what are postponed. We also analyze the theoretical properties of the proposed controller. Finally, we use a set of simulations to illustrate the approach