Zobrazeno 1 - 10
of 364
pro vyhledávání: '"D'Andrea, Raffaello"'
We present a nonlinear non-convex model predictive control approach to solving a real-world labyrinth game. We introduce adaptive nonlinear constraints, representing the non-convex obstacles within the labyrinth. Our method splits the computation-hea
Externí odkaz:
http://arxiv.org/abs/2406.08650
Distributed tactile sensing for multi-force detection is crucial for various aerial robot interaction tasks. However, current contact sensing solutions on drones only exploit single end-effector sensors and cannot provide distributed multi-contact se
Externí odkaz:
http://arxiv.org/abs/2401.17149
Autor:
Bi, Thomas, D'Andrea, Raffaello
Motivated by the challenge of achieving rapid learning in physical environments, this paper presents the development and training of a robotic system designed to navigate and solve a labyrinth game using model-based reinforcement learning techniques.
Externí odkaz:
http://arxiv.org/abs/2312.09906
Grasping objects whose physical properties are unknown is still a great challenge in robotics. Most solutions rely entirely on visual data to plan the best grasping strategy. However, to match human abilities and be able to reliably pick and hold unk
Externí odkaz:
http://arxiv.org/abs/2109.11504
This paper presents an offset-free model predictive controller for fast and accurate control of a spherical soft robotic arm. In this control scheme, a linear model is combined with an online disturbance estimation technique to systematically compens
Externí odkaz:
http://arxiv.org/abs/2103.07379
In this thesis we are interested in applying distributed estimation, control and optimization techniques to enable a group of quadcopters to fly through openings. The quadcopters are assumed to be equipped with a simulated bearing and distance sensor
Externí odkaz:
http://arxiv.org/abs/2102.07107
This paper aims to show that robots equipped with a vision-based tactile sensor can perform dynamic manipulation tasks without prior knowledge of all the physical attributes of the objects to be manipulated. For this purpose, a robotic system is pres
Externí odkaz:
http://arxiv.org/abs/2101.02680
The images captured by vision-based tactile sensors carry information about high-resolution tactile fields, such as the distribution of the contact forces applied to their soft sensing surface. However, extracting the information encoded in the image
Externí odkaz:
http://arxiv.org/abs/2012.11295
Sensory feedback is essential for the control of soft robotic systems and to enable deployment in a variety of different tasks. Proprioception refers to sensing the robot's own state and is of crucial importance in order to deploy soft robotic system
Externí odkaz:
http://arxiv.org/abs/2012.06413
This paper presents the application of a learning control approach for the realization of a fast and reliable pick-and-place application with a spherical soft robotic arm. The arm is characterized by a lightweight design and exhibits compliant behavi
Externí odkaz:
http://arxiv.org/abs/2011.04624