VP-STO: Via-point-based Stochastic Trajectory Optimization for Reactive Robot Behavior

Jankowski, Julius; Brudermüller, Lara; Hawes, Nick; Calinon, Sylvain

doi:10.48550/arxiv.2210.04067

Cited by 3 publications

(4 citation statements)

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“…A different class of methods for motion planning and collision avoidance is composed of so-called sample-based planning algorithms [14]; according to these approaches, the environment is randomly sampled using techniques such as probabilistic road maps or exploring random trees. An example is given in [15], where sampled via-points are transformed into a set of candidate collision-free trajectories subject to predefined kinodynamic limits. In [16], if a moving obstacle collides with the manipulator, the motion is locally re-planned by using a Bi-RRT-based algorithm connecting the current robot position with a target on the unperturbed trajectory.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Online Motion Planning for Safe Human–Robot Cooperation Using B-Splines and Hidden Markov Models

Braglia,

Tagliavini,

Pini

et al. 2023

Robotics

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When humans and robots work together, ensuring safe cooperation must be a priority. This research aims to develop a novel real-time planning algorithm that can handle unpredictable human movements by both slowing down task execution and modifying the robot’s path based on the proximity of the human operator. To achieve this, an efficient method for updating the robot’s motion is developed using a two-fold control approach that combines B-splines and hidden Markov models. This allows the algorithm to adapt to a changing environment and avoid collisions. The proposed framework is thus validated using the Franka Emika Panda robot in a simple start–goal task. Our algorithm successfully avoids collision with the moving hand of an operator monitored by a fixed camera.

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Section: Related Workmentioning

confidence: 99%

“…Spline functions are extensively used for generating smooth and optimal time trajectories in robotic applications [15,29,30]. B-splines are a particular representation of generic spline curves based on a linear combination of N basis functions [29], i.e.,…”

Section: Spatial Encoding Based On B-splinesmentioning

confidence: 99%

Online Motion Planning for Safe Human–Robot Cooperation Using B-Splines and Hidden Markov Models

Braglia,

Tagliavini,

Pini

et al. 2023

Robotics

View full text Add to dashboard Cite

show abstract

“…A different class of methods for motion planning and collision avoidance is composed of so-called sample-based planning algorithms [12]; according to these approaches, the environment is randomly sampled using techniques such as probabilistic road maps or exploring random trees. An example is given in [13], where sampled-via points are transformed into a set of candidate collision-free trajectories subject to predefined kinodynamic limits. In [14], if a moving obstacle will collide with the manipulator, the motion is locally replanned by using a Bi-RRT-based algorithm connecting the current robot position with a target on the unperturbed trajectory.…”

Section: A Related Workmentioning

confidence: 99%

“…Spline functions are extensively used for generating smooth and optimal-time trajectories in robotic applications [13] [25] [26]. B-Splines are a particular representation of generic spline curves based on a linear combination of N basis functions [25], i.e.…”

Section: A Spatial Encoding Based On B-splinesmentioning

confidence: 99%

Online Motion Planning for Safe Human-Robot Cooperation using B-Splines and Hidden Markov Models

Braglia¹,

Tagliavini²,

Pini³

et al. 2023

Preprint

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<p>When humans and robots work together, ensuring safe cooperation must be a priority. This research aims to develop a novel real-time planning algorithm that can handle unpredictable human movements by both slowing down task execution and modifying the robot's path based on the proximity of the human operator. To achieve this, an efficient method for updating the robot's motion is developed using a two-fold control approach that combines B-Splines and Hidden Markov Models. This allows the algorithm to adapt to a changing environment and avoid collisions. The proposed framework is thus validated using the Franka Emika Panda robot in a simple start-goal task. Our algorithm successfully avoids collision with the moving hand of an operator monitored by a fixed camera.</p>

show abstract

Online Motion Planning for Safe Human-Robot Cooperation using B-Splines and Hidden Markov Models

Braglia¹,

Tagliavini²,

Pini³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

VP-STO: Via-point-based Stochastic Trajectory Optimization for Reactive Robot Behavior

Cited by 3 publications

References 0 publications

Online Motion Planning for Safe Human–Robot Cooperation Using B-Splines and Hidden Markov Models

Online Motion Planning for Safe Human–Robot Cooperation Using B-Splines and Hidden Markov Models

Online Motion Planning for Safe Human-Robot Cooperation using B-Splines and Hidden Markov Models

Online Motion Planning for Safe Human-Robot Cooperation using B-Splines and Hidden Markov Models

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