Adaptive bipedal walking on slopes

06 September 2010

share this:

Imagine walking on a flat surface with your eyes blinded. If the slope below your feet changes, you’ll most likely change your posture to keep moving. To explain this, an idea from the 1950s says that we can predict the sensation that will be produced by a motor command sent by our central nervous system. We can therefore tell apart sensations that are due to our own motion and sensations due to external stimuli. When the expected sensation doesn’t match the sensory input, we change our behavior to compensate.

In work by Schröder-Schetelig et al., a robotic walker uses this idea to stay on its two feet. More precisely, the robot uses a neural network (which is a type of controller) to send commands to hip-joint and knee-joint motors such that the robot is able to walk on flat terrain. These motor commands are then copied (efference copy) and fed to a second neural network that captures the internal model of the robot. This model predicts the acceleration the robot should feel given its motor command and current state. If the acceleration is larger than expected, the robot is probably going downhill and should lean back to slow down. Likewise, if the acceleration is lower, the robot is going uphill and should lean forward. Leaning backward and forward is performed by moving a mass that represents the upper body of the robot and is controlled by a third neural network that takes as an input the robot’s predicted acceleration and the measured acceleration given by an accelerometer.

Experiments shown in the video below were conducted on Runbot, a 23cm bipedal robot that is physically constrained to a circular path of 1m radius and can not perform sideway movements. Results show the robot successfully climbing a changing slope.

In the future, Schröder-Schetelig et al. hope to refine the internal model of Runbot, make it climb even steeper slopes and adapt to new and unforeseen environments.

Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory
Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory

Related posts :




Origin Story of the OAK-D, with Brandon Gilles

Brandon Gilles, the founder of Luxonis and maker of the OAK-D, describes the journey and the flexibility of the OAK-D line of products
01 July 2022, by

The one-wheel Cubli

Researchers Matthias Hofer, Michael Muehlebach and Raffaello D’Andrea have developed the one-wheel Cubli, a three-dimensional pendulum system that can balance on its pivot using a single reaction wheel. How is it possible to stabilize the two tilt angles of the system with only a single reaction wheel?
30 June 2022, by and

At the forefront of building with biology

Raman is, as she puts it, “a mechanical engineer through and through.” Today, Ritu Raman leads the Raman Lab and is an Assistant Professor in the Department of Mechanical Engineering.
28 June 2022, by

Hot Robotics Symposium celebrates UK success

An internationally leading robotics initiative that enables academia and industry to find innovative solutions to real world challenges, celebrated its success with a Hot Robotics Symposium hosted across three UK regions last week.
25 June 2022, by

Researchers release open-source photorealistic simulator for autonomous driving

MIT scientists unveil the first open-source simulation engine capable of constructing realistic environments for deployable training and testing of autonomous vehicles.
22 June 2022, by

In this episode, Audrow Nash speaks to Maria Telleria, who is a co-founder and the CTO of Canvas. Canvas makes a drywall finishing robot and is based in the Bay Area. In this interview, Maria talks ab...
21 June 2022, by and

©2021 - ROBOTS Association


©2021 - ROBOTS Association