619 research outputs found
Supervised Autonomous Locomotion and Manipulation for Disaster Response with a Centaur-like Robot
Mobile manipulation tasks are one of the key challenges in the field of
search and rescue (SAR) robotics requiring robots with flexible locomotion and
manipulation abilities. Since the tasks are mostly unknown in advance, the
robot has to adapt to a wide variety of terrains and workspaces during a
mission. The centaur-like robot Centauro has a hybrid legged-wheeled base and
an anthropomorphic upper body to carry out complex tasks in environments too
dangerous for humans. Due to its high number of degrees of freedom, controlling
the robot with direct teleoperation approaches is challenging and exhausting.
Supervised autonomy approaches are promising to increase quality and speed of
control while keeping the flexibility to solve unknown tasks. We developed a
set of operator assistance functionalities with different levels of autonomy to
control the robot for challenging locomotion and manipulation tasks. The
integrated system was evaluated in disaster response scenarios and showed
promising performance.Comment: In Proceedings of IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS), Madrid, Spain, October 201
Fast Object Learning and Dual-arm Coordination for Cluttered Stowing, Picking, and Packing
Robotic picking from cluttered bins is a demanding task, for which Amazon
Robotics holds challenges. The 2017 Amazon Robotics Challenge (ARC) required
stowing items into a storage system, picking specific items, and packing them
into boxes. In this paper, we describe the entry of team NimbRo Picking. Our
deep object perception pipeline can be quickly and efficiently adapted to new
items using a custom turntable capture system and transfer learning. It
produces high-quality item segments, on which grasp poses are found. A planning
component coordinates manipulation actions between two robot arms, minimizing
execution time. The system has been demonstrated successfully at ARC, where our
team reached second places in both the picking task and the final stow-and-pick
task. We also evaluate individual components.Comment: In: Proceedings of the International Conference on Robotics and
Automation (ICRA) 201
Audio-based Roughness Sensing and Tactile Feedback for Haptic Perception in Telepresence
Haptic perception is highly important for immersive teleoperation of robots,
especially for accomplishing manipulation tasks. We propose a low-cost haptic
sensing and rendering system, which is capable of detecting and displaying
surface roughness. As the robot fingertip moves across a surface of interest,
two microphones capture sound coupled directly through the fingertip and
through the air, respectively. A learning-based detector system analyzes the
data in real time and gives roughness estimates with both high temporal
resolution and low latency. Finally, an audio-based vibrational actuator
displays the result to the human operator. We demonstrate the effectiveness of
our system through lab experiments and our winning entry in the ANA Avatar
XPRIZE competition finals, where briefly trained judges solved a
roughness-based selection task even without additional vision feedback. We
publish our dataset used for training and evaluation together with our trained
models to enable reproducibility of results.Comment: IEEE International Conference on Systems, Man, and Cybernetics (SMC),
Honolulu, Hawaii, USA, October 202
Robust Immersive Telepresence and Mobile Telemanipulation: NimbRo wins ANA Avatar XPRIZE Finals
Robotic avatar systems promise to bridge distances and reduce the need for
travel. We present the updated NimbRo avatar system, winner of the $5M grand
prize at the international ANA Avatar XPRIZE competition, which required
participants to build intuitive and immersive robotic telepresence systems that
could be operated by briefly trained operators. We describe key improvements
for the finals, compared to the system used in the semifinals: To operate
without a power- and communications tether, we integrated a battery and a
robust redundant wireless communication system. Video and audio data are
compressed using low-latency HEVC and Opus codecs. We propose a new locomotion
control device with tunable resistance force. To increase flexibility, the
robot's upper-body height can be adjusted by the operator. We describe
essential monitoring and robustness tools which enabled the success at the
competition. Finally, we analyze our performance at the competition finals and
discuss lessons learned.Comment: M. Schwarz and C. Lenz contributed equall
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