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

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Autonomous Exploration of Subterranean Environments

Published on Mar 26, 2019

ANYmal, a quadrupedal robot developed by RSL (ETH Zurich) and ANYbotics, is deployed in subterranean environments. The legged robot explores an unknown area while creating a 3D representation of the surroundings.

Credits:
Marco Tranzatto, Fabian Tresoldi, Fabian Jenelten, Giorgio Valsecchi, Russell Buchanan, Marko Bjelonic, Jan Carius, Lorenz Wellhausen, Kai Holtmann, Marco Hutter.

 

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Trajectory optimization for wheeled-legged quadrupedal robots using linearized ZMP Constraints

Published on Mar 28, 2019

We present a trajectory optimizer for quadrupedal robots with actuated wheels. By solving for angular, vertical, and planar components of the base and feet trajectories in a cascaded fashion and by introducing a novel linear formulation of the zero-moment point (ZMP) balance criterion, we rely on quadratic programming only, thereby eliminating the need for nonlinear optimization routines. Yet, even for gaits containing full flight phases, we are able to generate trajectories for executing complex motions that involve simultaneous driving, walking, and turning. We verified our approach in simulations of the quadrupedal robot ANYmal equipped with wheels, where we are able to run the proposed trajectory optimizer at 50 Hz. To the best of our knowledge, this is the first time that such dynamic motions are demonstrated for wheeled-legged quadrupedal robots using an online motion planner.

Paper accepted to IEEE Robotics and Automation Letters (RA-L) and IEEE International Conference on Robotics and Automation (ICRA) 2019 in Montreal, Canada:
"Trajectory Optimization for Wheeled-Legged Quadrupedal Robots using Linearized ZMP Constraints"

Authors: Yvain de Viragh, Marko Bjelonic, C. Dario Bellicoso, Fabian Jenelten, and Marco Hutter

 

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Dynamic locomotion on slippery ground

Published on Jul 27, 2019

Dynamic locomotion on unstructured and uneven terrain is a challenging task in legged robotics. Especially when it comes to slippery ground conditions, common state estimation and control algorithms suffer from the usual no-slip assumption. In fact, there has been only little research on this subject. This paper addresses the problem of slipping by treating slip detection and recovery tasks separately. Our contribution to the former is a probabilistic slip state estimator based on a Hidden Markov Model. In the second part of this paper, we propose impedance control and friction modulation as useful tools to recover stability during traction loss. We demonstrate the success of our estimation/control architecture by enabling ANYmal, a quadrupedal torque-controllable robot, to dynamically walk over slippery terrain.

Paper accepted to IEEE Robotics and Automation Letters (RA-L) and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019).

Authors: Fabian Jenelten, Jemin Hwangbo, C. Dario Bellicoso, Fabian Tresoldi and Marco Hutter.

 

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ANYmal C legged robot – the next step in robotic industrial inspection

Published on Aug 20, 2019

ANYbotics, a pioneering Swiss robotics company, introduces a new generation of its autonomous legged robot. Named ANYmal C, this robot is optimized for industrial inspection tasks where it can provide high availability, safety, and reliability for automated routine inspections with a wide range of sensors.

# Industrial Inspection with Mobile Robots

Autonomous mobile robots will revolutionize industrial inspection. Executing pre-defined missions, autonomous systems can safely and reliably navigate through industrial plants and carry sensors to collect and interpret equipment and environment data.

To navigate the complex infrastructure of industrial plants, ANYbotics introduces their next-generation autonomous legged robot ANYmal C. Built around the superior mobility of four legs, ANYmal C can move through industrial environments including steps and stairs without the need for any adaptations to a facility. Carrying a variety of sensors such as visual and thermal cameras, LIDAR, microphones, and gas detection sensors, ANYmal perceives and interprets a broad range of physical properties. The system evaluates instruments, checks for the status of objects, detects hotspots, and senses gases – even in situations that are threatening to human inspectors.

# ANYmal C – The Next Step

The ANYbotics team has been building legged robots for more than ten years and developed the new generation ANYmal C from the feet up based on industry requirements. At the core, powerful torque-controllable actuators have been designed to carry the robot over steep stairs and to reliably take the strain of over a million cycles. LIDAR and depth cameras provide a 360-degree high precision view of the robot’s environment. Teleoperation is simplified by integrated wide-angle cameras and an industrial-grade remote control. Intel i7 Hexa-core processors deliver the computation power for advanced locomotion control, real-time mapping, autonomous navigation, and for sophisticated on-board custom applications. These features are enclosed in a user-friendly, ruggedized, and fully water- and dustproof IP67 design. ANYmal C carries up to 10 kg in payload, and after two hours of operations on a single battery charge, the robot autonomously connects to a docking station for recharging.

# Awaited by the Industry

The energy, oil & gas, processing, and many other industries have been eagerly awaiting mobile robotic solutions to improve safety and efficiency in their operations. Due to their high complexity, industrial plants are difficult to operate without failures, and due to high downtime costs, plant operators are very keen to avoid interruptions. To prevent equipment from failing, plants need to be monitored and inspected regularly, and manual data collection by human inspectors is a tedious and error-prone task in a potentially dangerous environment. Even if parts of the equipment are sensorized, defects such as leakages, rust, hotspots, or missing equipment are challenging to detect. For this reason, autonomous mobile robots will fundamentally change the inspection strategy of operators and allow for optimized plant architectures in the future.

# The Way Forward

ANYmal C is a pioneering system ready to be tested on industrial sites. To explore the potential of autonomous robotic inspection, ANYbotic provides test installations and pilot projects worldwide to prepare for completely unsupervised installations in the future. ANYmal C is available for sale to development customers, engineering partners, and universities including a complete software and simulation environment. First ANYmal C robots will be ready for shipment before the end of the year.

 

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Rolling in the Deep – Hybrid locomotion for wheeled-legged robots

Published on Sep 16, 2019

Our quadrupedal robot ANYmal equipped with actuated wheels performs dynamic hybrid walking-driving motions.

 

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Roller-walking ANYmal live at Digital Day 2019

Oct 10, 2019

Roller-Walking ANYmal performing live on stage at Digital Day 2019 in Zurich.

 

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Feedback MPC for torque-controlled legged robots

Nov 6, 2019

Authors: Ruben Grandia, Farbod Farshidian, René Ranftl, Marco Hutter.
PDF: https://arxiv.org/abs/1905.06144
Abstract:
The computational power of mobile robots is currently insufficient to achieve torque level whole-body Model Predictive Control (MPC) at the update rates required for complex dynamic systems such as legged robots. This problem is commonly circumvented by using a fast tracking controller to compensate for model errors between updates. In this work, we show that the feedback policy from a Differential Dynamic Programming (DDP) based MPC algorithm is a viable alternative to bridge the gap between the low MPC update rate and the actuation command rate. We propose to augment the DDP approach with a relaxed barrier function to address inequality constraints arising from the friction cone. A frequency-dependent cost function is used to reduce the sensitivity to high-frequency model errors and actuator bandwidth limits. We demonstrate that our approach can find stable locomotion policies for the torque-controlled quadruped, ANYmal, both in simulation and on hardware.

 

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Graph-based path planner: ANYmal quadruped robot exploring a bunker

Feb 5, 2020

In this video we present results on autonomous subterranean exploration inside an underground bunker using the ANYmal legged robot. ANYmal is utilizing the proposed Graph-based Exploration Path Planner which operates on the basis of the birfurcaton between a local and a global planning stage.

In this field experiment, the local planner guides the robot through rooms and corridors of the underground bunker, while the global planner automatically derives and commands a collision-free return-to-home path at the end of the mission.

 

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ANYmal quadrupedal robot exploring Satsop Business Park

Apr 9, 2020

In this video we present results on autonomous subterranean exploration inside an unfinished nuclear power plant in Washington, USA, using the ANYmal quadrupedal robot.

ANYmal was tasked with autonomously exploring an unknown environment surrounding the reactor, during an activity of the DARPA Subterranean Challenge - Urban Circuit.

The presented work has been conducted in collaboration with the partners of team CERBERUS.

Credits: Marco Tranzatto, Samuel Zimmermann, Marko Bjelonic, Lorenz Wellhausen, Timon Homberger, Fabian Jenelten, Markus Montenegro, Takahiro Miki, Joonho Lee, Giorgio Valsecchi, Jan Carius, Fabian Tresoldi, Marco Hutter.

 

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Trajectory optimization for wheeled-legged quadrupedal robots driving in challenging terrain

Apr 29, 2020

Wheeled-legged robots are an attractive solution for versatile locomotion in challenging terrain. They combine the speed and efficiency of wheels with the ability of legs to traverse challenging terrain. In this paper, we present a trajectory optimization formulation for wheeled-legged robots that optimizes over the base and wheels' positions and forces and takes into account the terrain information while computing the plans. This enables us to find optimal driving motions over challenging terrain. The robot is modeled as a single rigid-body, which allows us to plan complex motions and still keep a low computational complexity to solve the optimization quickly. The terrain map, together with the use of a stability constraint, allows the optimizer to generate feasible motions that cannot be discovered without taking the terrain information into account. The optimization is formulated as a Nonlinear Programming problem and the reference motions are tracked by a hierarchical whole-body controller that computes the torque actuation commands for the robot. The trajectories have been experimentally verified on quadrupedal robot ANYmal equipped with non-steerable torque-controlled wheels. Our trajectory optimization framework enables wheeled quadrupedal robots to drive over challenging terrain, e.g., steps, slopes, stairs, while negotiating these obstacles with dynamic motions.

Full paper: "Trajectory Optimization for Wheeled-Legged Quadrupedal Robots Driving in Challenging Terrain"

Authors: Vivian S. Medeiros, Edo Jelavic, Marko Bjelonic, Roland Siegwart, Marco A. Meggiolaro and Marco Hutter

 

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Quadrupedal locomotion on uneven terrain with sensorized feet

May 27, 2020

Video submission for ICRA 2020: Quadrupedal locomotion on uneven terrain with sensorized feet

Paper: https://doi.org/10.1109/LRA.2020.2969160

Paper Abstract:
Sensing of the terrain shape is crucial for legged robots deployed in the real world since the knowledge of the local terrain inclination at the contact points allows for an optimized force distribution that minimizes the risk of slipping. In this letter, we present a reactive locomotion strategy for torque controllable quadruped robots based on sensorized feet. Since the present approach works without exteroceptive sensing, it is robust against degraded vision. Inertial and force/torque sensors implemented in specially designed feet with articulated passive ankle joints measure the local terrain inclination and interaction forces. The proposed controller exploits the contact null-space in order to minimize the tangential forces to prevent slippage even in case of extreme contact conditions. We experimentally tested the proposed method in laboratory experiments and validated the approach with the quadrupedal robot ANYmal.

 

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Towards autonomous inspection of concrete deterioration in sewers with legged robots

Jun 1, 2020

We demonstrate a method to assess the concrete deterioration in sewers by performing a tactile inspection motion with a sensorized foot of a legged robot.

Title: Towards autonomous inspection of concrete deterioration in sewers with legged robots

Authors: Hendrik Kolvenbach, David Wisth, Russell Buchanan, Giorgio Valsecchi, Ruben Grandia, Maurice Fallon, Marco Hutter

 

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This robot can tell when sewers need repairing by scratching the walls

Jun 5, 2020

A four-legged robot that inspects concrete can walk through underground sewage tunnels and detect when they need repairing.

Hendrik Kolvenbach at the Swiss Federal Institute of Technology (ETH Zurich) in Switzerland and his colleagues have developed a robot that scratches one of its legs against concrete to determine the condition it is in.

"This robot can tell when sewers need repairing by scratching the walls"

by Donna Lu
June 4, 2020

 

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Perceptive whole body planning for multi-legged robots in confined spaces

Jun 15, 2020

Legged robots are exceedingly versatile and have the potential to navigate complex, confined spaces due to their many degrees of freedom. As a result of the computational complexity, there exist no online planners for perceptive whole-body locomotion of robots in tight spaces. In this paper, we present a new method for perceptive planning for multi-legged robots, which generates body poses, footholds, and swing trajectories for collision avoidance. Measurements from an onboard depth camera are used to create a 3D map of the terrain around the robot. We randomly sample body poses then smooth the resulting trajectory while satisfying several constraints such as robot kinematics and collision avoidance. Footholds and swing trajectories are computed based on the terrain, and the robot body pose is optimized to ensure stable locomotion while not colliding with the environment. Our method is designed to run online on a real robot and generate trajectories several meters long. We first tested our algorithm in several simulations with varied confined spaces using the quadrupedal robot ANYmal. We also simulated experiments with the hexapod robot Weaver to demonstrate applicability to different legged robot configurations. Then, we demonstrated our whole body planner in several online experiments both indoors and in realistic scenarios at an emergency rescue training facility. ANYmal, which has a nominal standing height of 80 cm and width of 59 cm, navigated through several representative disaster areas with openings as small as 60 cm. 3 m trajectories were re-planned with 500 ms update times.


Article accepted for Journal of Field Robotics
Authors: Russell Buchanan, Lorenz Wellhausen, Marko Bjelonic, Tirthankar Bandyopadhyay, Navinda Kottege, Marco Hutter

 

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ANYmal C legged robot showcase

Jul 8, 2020

ANYmal C, 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 analogue sensors and monitors the environment.

 

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Haptic sequential Monte Carlo localization for quadrupedal locomotion in vision-denied scenarios

Jul 23, 2020

by Russell Buchanan, Marco Camurri, Maurice Fallon

Continuous robot operation in extreme scenarios such as underground mines or sewers is difficult because exteroceptive sensors may fail due to fog, darkness, dirt or malfunction. So as to enable autonomous navigation in these kinds of situations, we have developed a type of proprioceptive localization which exploits the foot contacts made by a quadruped robot to localize against a prior map of an environment, without the help of any camera or LIDAR sensor. The proposed method enables the robot to accurately re-localize itself after making a sequence of contact events over a terrain feature. The method is based on Sequential Monte Carlo and can support both 2.5D and 3D prior map representations. We have tested the approach online and onboard the ANYmal quadruped robot in two different scenarios: the traversal of a custom built wooden terrain course and a wall probing and following task. In both scenarios, the robot is able to effectively achieve a localization match and to execute a desired pre-planned path. The method keeps the localization error down to 10cm on feature rich terrain by only using its feet, kinematic and inertial sensing.

 

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Perceptive locomotion in rough terrain - Online foothold optimization

Aug 7, 2020

Paper Abstract:

Compared to wheeled vehicles, legged systems have a vast potential to traverse challenging terrain. To exploit the full potential, it is crucial to tightly integrate terrain perception for foothold planning. We present a hierarchical locomotion planner together with a foothold optimizer that finds locally optimal footholds within an elevation map. The map is generated in real-time from on-board depth sensors. We further propose a terrain-aware contact schedule to deal with actuator velocity limits. We validate the combined locomotion pipeline on our quadrupedal robot ANYmal with a variety of simulated and real-world experiments. We show that our method can cope with stairs and obstacles of heights up to 33 % of the robot’s leg length.


The paper is accepted to IEEE Robotics and Automation Letters (RA-L) and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020).

 

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Whole-body MPC and online gait sequence generation for wheeled-legged robots

Oct 12, 2020

Our roller-walking robot ANYmal equipped with actuated wheels performs hybrid locomotion in challenging environments.

 

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ANYmal tackles construction safety

Oct 20, 2020

ANYbotics partnered with Losinger Marazzi to explore ANYmal’s potential of patrolling construction sites to identify and report safety issues. With such a complex environment, only a robot designed to navigate difficult terrain is able to bring digitalization to such a physically demanding industry.

 

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Learning quadrupedal locomotion over challenging terrain

Oct 21, 2020

We present a radically robust locomotion controller for quadrupedal robots which is trained using reinforcement learning in simulation. It uses no external sensing like cameras or Lidar and relies only on internal sensors like IMU and joint encoders.