Quadruped robots have become increasingly capable on ground-level challenges, from stairs to uneven terrain. Ladders remain a harder problem, even though they are common in factories and other industrial environments where these robots may be deployed.
Why ladders are a difficult step for quadruped robots
Robots like Boston Dynamics' Spot have helped show why four-legged systems are useful. They can move over small obstacles, climb stairs, and handle surfaces that are not perfectly flat.
That versatility matters in industrial settings, where floors, platforms, and routes are rarely as simple as a clean lab path. But a ladder is not just another uneven surface. It requires the robot to place its limbs precisely, grip or hook onto narrow rungs, and keep its body stable while moving upward.
The challenge is especially important because ladders are described as ever present in factories and other industrial environments. If quadruped robots are limited to nominal terrain and cannot handle basic infrastructure, their usefulness in those sites remains narrower.
ETH Zurich's approach uses ANYMal and hooked end effectors
ETH Zurich has demonstrated a path forward using the ANYMal robot from its spinoff, ANYbotics. The research builds on the school's recent work in quadrupedal robot research and focuses on making a four-legged robot handle a structure that has been difficult for this class of machine.
The team outfitted ANYMal with specialty end effectors designed to hook onto ladder rungs. That hardware matters because a standard foot is not naturally shaped for the task. A rung offers a small contact point, and the robot needs a reliable way to connect with it as it climbs.
Earlier attempts at ladder climbing mostly involved bipedal humanoid-style robots and specialty ladders, according to the school. Those approaches also proved too slow to be effective. ETH Zurich's work points to a different route: adapt the quadruped's contact with the ladder and pair that hardware with a control system that can respond to variation.
Reinforcement learning helps the robot adapt
The hardware is only part of the system. The key control element is reinforcement learning, which helps the robot adjust to the peculiarities of different ladders.
That adaptability is central because ladders are not all identical in how they feel to a robot. The system needs to deal with the timing of each movement, the placement of each limb, and the stability of the climb as it moves from rung to rung.
The researchers describe the broader significance this way:
“This work expands the scope of industrial quadruped robot applications beyond inspection on nominal terrains to challenging infrastructural features in the environment,” the researchers write, “highlighting synergies between robot morphology and control policy when performing complex skills.”
In plain terms, the work is not just about making a robot perform a single impressive trick. It is about combining body design and control policy so a quadruped can manage a feature of the built environment that would otherwise block it.
The reported results show speed and reliability gains
ETH Zurich says the combined system achieved a 90% success rate when navigating ladder angles in the 70- to 90-degree range. The school also reports a climbing speed increase of 232x versus current state-of-the-art systems.
Those two details are important together. A ladder-climbing robot that is fast but unreliable would have limited value. A robot that succeeds but moves too slowly may also struggle to be practical in industrial environments.
The system can also correct itself in real time. If it misjudges a rung or gets the timing of a step wrong, it can adjust its climb rather than simply failing at the first error.
The source points to several core pieces of the advance:
- ANYMal is used as the quadruped platform.
- Specialty end effectors hook onto ladder rungs.
- Reinforcement learning helps the robot adapt to different ladders.
- The system reports a 90% success rate across ladder angles in the 70- to 90-degree range.
- The school reports a 232x speed increase versus current state-of-the-art systems.
What this could mean for industrial robot use
The immediate implication is a broader operating range for industrial quadruped robots. These machines have already shown strength on stairs, obstacles, and uneven ground, but ladders have remained a serious limitation.
If a quadruped robot can climb ladders more effectively, it can potentially move through more of the same environments where it is already expected to operate. The source frames this as a move beyond inspection on nominal terrains and toward challenging infrastructural features.
That distinction matters. Nominal terrain is the easy case. Industrial environments often include features that were built for people, not robots. Ladders are a clear example of that gap.
ETH Zurich's demonstration does not remove every problem from industrial robot deployment. But it shows how a targeted combination of robot morphology and learning-based control can address a specific barrier. For quadruped robots, the ladder may be becoming less of a dead end and more of another part of the route.