878 research outputs found
An optimization approach for the inverse kinematics of a highly redundant robot
This paper describes a robot with 12 degrees of freedom for pick-and-place operations using bricks. In addition, an optimization approach is proposed, which determines the state of each joint (that establishes the pose for the robot) based on the target position while minimizing the effort of the servomotors avoiding the inverse kinematics problem, which is a hard task for a 12 DOF robot manipulator. Therefore, it is a multi-objective optimization problem that will be solved using two optimization methods: the Stretched Simulated Annealing method and the NSGA II method.
The experiments conducted in a simulation environment prove that the proposed approach is able to determine a solution for the inverse kinematics problem. A real robot formed by several servomotors and a gripper is also presented in this research for validating the solutions.info:eu-repo/semantics/publishedVersio
Design and analysis of a wire-driven flexible manipulator for bronchoscopic interventions
Bronchoscopic interventions are widely performed for the diagnosis and treatment of lung diseases. However, for most endobronchial devices, the lack of a bendable tip restricts their access ability to get into distal bronchi with complex bifurcations. This paper presents the design of a new wire-driven continuum manipulator to help guide these devices. The proposed manipulator is built by assembling miniaturized blocks that are featured with interlocking circular joints. It has the capability of maintaining its integrity when the lengths of actuation wires change due to the shaft flex. It allows the existence of a relatively large central cavity to pass through other instruments and enables two rotational degrees of freedom. All these features make it suitable for procedures where tubular anatomies are involved and the flexible shafts have to be considerably bent in usage, just like bronchoscopic interventions. A kinematic model is built to estimate the relationship between the translations of actuation wires and the manipulator tip position. A scale-up model is produced for evaluation experiments and the results validate the performance of the proposed mechanism
Handling robot constraints within a Set-Based Multi-Task Priority Inverse Kinematics Framework
Set-Based Multi-Task Priority is a recent framework to handle inverse
kinematics for redundant structures. Both equality tasks, i.e., control
objectives to be driven to a desired value, and set-bases tasks, i.e., control
objectives to be satisfied with a set/range of values can be addressed in a
rigorous manner within a priority framework. In addition, optimization tasks,
driven by the gradient of a proper function, may be considered as well, usually
as lower priority tasks. In this paper the proper design of the tasks, their
priority and the use of a Set-Based Multi-Task Priority framework is proposed
in order to handle several constraints simultaneously in real-time. It is shown
that safety related tasks such as, e.g., joint limits or kinematic singularity,
may be properly handled by consider them both at an higher priority as
set-based task and at a lower within a proper optimization functional.
Experimental results on a 7DOF Jaco$^2
Quantifying the Evolutionary Self Structuring of Embodied Cognitive Networks
We outline a possible theoretical framework for the quantitative modeling of
networked embodied cognitive systems. We notice that: 1) information self
structuring through sensory-motor coordination does not deterministically occur
in Rn vector space, a generic multivariable space, but in SE(3), the group
structure of the possible motions of a body in space; 2) it happens in a
stochastic open ended environment. These observations may simplify, at the
price of a certain abstraction, the modeling and the design of self
organization processes based on the maximization of some informational
measures, such as mutual information. Furthermore, by providing closed form or
computationally lighter algorithms, it may significantly reduce the
computational burden of their implementation. We propose a modeling framework
which aims to give new tools for the design of networks of new artificial self
organizing, embodied and intelligent agents and the reverse engineering of
natural ones. At this point, it represents much a theoretical conjecture and it
has still to be experimentally verified whether this model will be useful in
practice.
Design, kinematics, and controlling a novel soft robot arm with parallel motion
This article presents a novel design for a double bend pneumatic muscle actuator (DB-PMA) inspired by snake lateral undulation. The presented actuator has the ability to bend in opposite directions from its two halves. This behavior results in horizontal and vertical movements of the actuator distal ends. The kinematics for the proposed actuator are illustrated and experiments conducted to validate its unique features. Furthermore, a continuum robot arm with the ability to move in parallel (horizontal displacement) is designed with a single DB-PMA and a two-finger soft gripper. The performance of the soft robot arm presented is explained, then another design of the horizontal motion continuum robot arm is proposed, using two self-bending contraction actuators (SBCA) in series to overcome the payload effects on the upper half of the soft arm
Dynamic Active Constraints for Surgical Robots using Vector Field Inequalities
Robotic assistance allows surgeons to perform dexterous and tremor-free
procedures, but robotic aid is still underrepresented in procedures with
constrained workspaces, such as deep brain neurosurgery and endonasal surgery.
In these procedures, surgeons have restricted vision to areas near the surgical
tooltips, which increases the risk of unexpected collisions between the shafts
of the instruments and their surroundings. In this work, our
vector-field-inequalities method is extended to provide dynamic
active-constraints to any number of robots and moving objects sharing the same
workspace. The method is evaluated with experiments and simulations in which
robot tools have to avoid collisions autonomously and in real-time, in a
constrained endonasal surgical environment. Simulations show that with our
method the combined trajectory error of two robotic systems is optimal.
Experiments using a real robotic system show that the method can autonomously
prevent collisions between the moving robots themselves and between the robots
and the environment. Moreover, the framework is also successfully verified
under teleoperation with tool-tissue interactions.Comment: Accepted on T-RO 2019, 19 Page
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