211 research outputs found
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
Active Constraints using Vector Field Inequalities for Surgical Robots
Robotic assistance allows surgeons to perform dexterous and tremor-free
procedures, but is still underrepresented in deep brain neurosurgery and
endonasal surgery where the workspace is constrained. In these conditions, the
vision of surgeons is restricted to areas near the surgical tool tips, which
increases the risk of unexpected collisions between the shafts of the
instruments and their surroundings, in particular in areas outside the surgical
field-of-view. Active constraints can be used to prevent the tools from
entering restricted zones and thus avoid collisions. In this paper, a vector
field inequality is proposed that guarantees that tools do not enter restricted
zones. Moreover, in contrast with early techniques, the proposed method limits
the tool approach velocity in the direction of the forbidden zone boundary,
guaranteeing a smooth behavior and that tangential velocities will not be
disturbed. The proposed method is evaluated in simulations featuring two eight
degrees-of-freedom manipulators that were custom-designed for deep
neurosurgery. The results show that both manipulator-manipulator and
manipulator-boundary collisions can be avoided using the vector field
inequalities.Comment: Accepted on ICRA 2018, 8 page
Adaptive Constrained Kinematic Control using Partial or Complete Task-Space Measurements
Recent advancements in constrained kinematic control make it an attractive
strategy for controlling robots with arbitrary geometry in challenging tasks.
Most current works assume that the robot kinematic model is precise enough for
the task at hand. However, with increasing demands and safety requirements in
robotic applications, there is a need for a controller that compensates online
for kinematic inaccuracies. We propose an adaptive constrained kinematic
control strategy based on quadratic programming, which uses partial or complete
task-space measurements to compensate online for calibration errors. Our method
is validated in experiments that show increased accuracy and safety compared to
a state-of-the-art kinematic control strategy.Comment: Accepted on T-RO 2022, 16 Pages. Corrected a few typos and adjusted
figure placemen
Calibration of spatial relationships between multiple robots and sensors
Classic hand-eye calibration methods have been limited to single robots and sensors. Recently a new calibration formulation for multiple robots has been proposed that solves for the extrinsic calibration parameters for each robot simultaneously instead of sequentially. The existing solutions for this new problem required data to have correspondence, but Ma, Goh and Chirikjian (MGC) proposed a probabilistic method to solve this problem which eliminated the need for correspondence. In this thesis, the literature of the various robot-sensor calibration problems and solutions are surveyed, and the MGC method is reviewed in detail. Lastly comparison with other methods using numerical simulations were carried out to draw some conclusions
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