ANYmal, quadrupedal robot, Robotic Systems Lab, Institute of Robotics and Intelligent Systems, Zurich, Switzerland

[Administrator]

The unrivaled performance of ANYmal: 24/7 in all weather

Dec 7, 2023

ANYmal, the autonomous legged robot designed for industrial challenging environments, provides the mobility, autonomy, and inspection intelligence to enable safe and efficient inspection operations. In this virtual showcase, discover how ANYmal climbs stairs, recovers from a fall, performs an autonomous mission and avoids obstacles, docks to charge by itself, digitizes analog sensors, and monitors the environment.

 

[Administrator]

ANYmal Unleashed: Revolutionizing Search-and-Rescue with Legged Robots

Jan 17, 2024

Explore the frontier of search-and-rescue capabilities of legged robots as ANYmal boldly steps into a disaster site training facility's challenging terrain. Uncover the immense potential of these robotic machines, offering a glimpse into the future of human-robot collaborations in critical and dangerous missions. Join us on this gripping journey where cutting-edge technology meets real-world challenges, forging a path toward safer and more efficient search-and-rescue operations.

 

[Administrator]

Pedipulate: enabling manipulation skills using a quadruped robot's leg

Feb 19, 2024

We present a learning-based control approach to enable manipulation skills with a quadruped robot's leg. The paper was accepted for publication at ICRA 2024.

Project website: sites.google.com/leggedrobotics.com/pedipulate
Paper: arxiv.org/abs/2402.10837

Authors: Philip Arm, Mayank Mittal, Hendrik Kolvenbach, Marco Hutter

 

[Administrator]

Scaling production beyond 1000 ANYmals with Zollner

Feb 16, 2024

Large industrial asset operators increasingly use robotics to automate hazardous work at their facilities. This has led to soaring demand for autonomous inspection solutions like ANYmal. Series production by our partner Zollner enables ANYbotics to supply our customers with the required quantities of robots.
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ANYmal, the autonomous legged robot designed for industrial challenging environments, provides the mobility, autonomy, and inspection intelligence to enable safe and efficient inspection operations. In this virtual showcase, discover how ANYmal climbs stairs, recovers from a fall, performs an autonomous mission and avoids obstacles, docks to charge by itself, digitizes analog sensors, and monitors the environment.

 

[Administrator]

ANYmal, the world’s first ex-proof legged robot

Premiered March 7, 2024

Speakers:
Belin Güngör
Business Development Manager
ANYbotics

Robots:
ANYmal
World’s first ex-proof legged robot
ANYbotics

The AI for Good Global Summit is the leading action-oriented United Nations platform promoting AI to advance health, climate, gender, inclusive prosperity, sustainable infrastructure, and other global development priorities. AI for Good is organized by the International Telecommunication Union (ITU) – the UN specialized agency for information and communication technology – in partnership with 40 UN sister agencies and co-convened with the government of Switzerland.

 

[Administrator]

ANYmal Parkour: Learning Agile Navigation for Quadrupedal Robots

Mar 13, 2024

In this video, we demonstrate how our fully-learned method enables robots to conquer challenging scenarios reminiscent of parkour challenges.

The paper introduces a hierarchical formulation that trains advanced locomotion skills for various obstacles, including walking, jumping, climbing, and crouching. A high-level policy is used to select and control these skills, allowing the robot to adapt its behavior based on the environment at hand. Furthermore, a perception module is trained to reconstruct obstacles from occluded and noisy sensory data, enhancing the robot's scene-understanding capabilities.

Unlike previous attempts, our method does not require expert demonstration, offline computation, prior knowledge of the environment, or explicit consideration of contacts. It achieves impressive results solely through training on simulated data.

Our real-world experiments showcase the successful transfer of these learned skills onto hardware.