Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Colledanchise, Michele"'
Publikováno v:
IEEE International Conference on Humanoid Robots, 2022
Many robotic tasks involving some form of 3D visual perception greatly benefit from a complete knowledge of the working environment. However, robots often have to tackle unstructured environments and their onboard visual sensors can only provide inco
Externí odkaz:
http://arxiv.org/abs/2209.04300
Publikováno v:
IEEE International Conference on Humanoid Robots, 2022
Action recognition is a fundamental capability for humanoid robots to interact and cooperate with humans. This application requires the action recognition system to be designed so that new actions can be easily added, while unknown actions are identi
Externí odkaz:
http://arxiv.org/abs/2209.04288
Publikováno v:
IEEE Transactions on Robotics, 2021
This paper addresses the concurrency issues affecting Behavior Trees (BTs), a popular tool to model the behaviors of autonomous agents in the video game and the robotics industry. BT designers can easily build complex behaviors composing simpler ones
Externí odkaz:
http://arxiv.org/abs/2110.11813
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Recent visual pose estimation and tracking solutions provide notable results on popular datasets such as T-LESS and YCB. However, in the real world, we can find ambiguous objects that do not allow exact classification and detection from a single view
Externí odkaz:
http://arxiv.org/abs/2108.00737
Autor:
Colledanchise, Michele, Cicala, Giuseppe, Domenichelli, Daniele E., Natale, Lorenzo, Tacchella, Armando
Publikováno v:
Robust and Reliable Autonomy in the Wild (R2AW) IJCAI 2021 Workshop
In this paper, we present a toolchain to design, execute, and verify robot behaviors. The toolchain follows the guidelines defined by the EU H2020 project RobMoSys and encodes the robot deliberation as a Behavior Tree (BT), a directed tree where the
Externí odkaz:
http://arxiv.org/abs/2106.15211
Publikováno v:
IEEE Robotics and Automation Letters, Volume 6, Issue 3, July 2021
There is a growing interest in Behavior Trees (BTs) as a tool to describe and implement robot behaviors. BTs were devised in the video game industry and their adoption in robotics resulted in the development of ad-hoc libraries to design and execute
Externí odkaz:
http://arxiv.org/abs/2106.15227
Autor:
Colledanchise, Michele, Cicala, Giuseppe, Domenichelli, Daniele E., Natale, Lorenzo, Tacchella, Armando
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
In this paper, we enable automated property verification of deliberative components in robot control architectures. We focus on formalizing the execution context of Behavior Trees (BTs) to provide a scalable, yet formally grounded, methodology to ena
Externí odkaz:
http://arxiv.org/abs/2106.12474
Autor:
Colledanchise, Michele
Robots applications in our daily life increase at an unprecedented pace. As robots will soon operate "out in the wild", we must identify the safety and security vulnerabilities they will face. Robotics researchers and manufacturers focus their attent
Externí odkaz:
http://arxiv.org/abs/2103.13268
Task planning in a probabilistic belief state domains allows generating complex and robust execution policies in those domains affected by state uncertainty. The performance of a task planner relies on the belief state representation. However, curren
Externí odkaz:
http://arxiv.org/abs/2008.10386
In this paper, we propose Belief Behavior Trees (BBTs), an extension to Behavior Trees (BTs) that allows to automatically create a policy that controls a robot in partially observable environments. We extend the semantic of BTs to account for the unc
Externí odkaz:
http://arxiv.org/abs/2008.09393