Robots that can adapt like animals

07/13/2014
by   Antoine Cully, et al.
0

As robots leave the controlled environments of factories to autonomously function in more complex, natural environments, they will have to respond to the inevitable fact that they will become damaged. However, while animals can quickly adapt to a wide variety of injuries, current robots cannot "think outside the box" to find a compensatory behavior when damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. Here we introduce an intelligent trial and error algorithm that allows robots to adapt to damage in less than two minutes, without requiring self-diagnosis or pre-specified contingency plans. Before deployment, a robot exploits a novel algorithm to create a detailed map of the space of high-performing behaviors: This map represents the robot's intuitions about what behaviors it can perform and their value. If the robot is damaged, it uses these intuitions to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a compensatory behavior that works in spite of the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new technique will enable more robust, effective, autonomous robots, and suggests principles that animals may use to adapt to injury.

READ FULL TEXT

page 2

page 3

page 4

page 11

page 12

page 13

research
10/13/2016

Reset-free Trial-and-Error Learning for Robot Damage Recovery

The high probability of hardware failures prevents many advanced robots ...
research
10/05/2016

Towards semi-episodic learning for robot damage recovery

The recently introduced Intelligent Trial and Error algorithm (IT&E) ena...
research
02/02/2013

Fast Damage Recovery in Robotics with the T-Resilience Algorithm

Damage recovery is critical for autonomous robots that need to operate f...
research
04/12/2022

Hierarchical Quality-Diversity for Online Damage Recovery

Adaptation capabilities, like damage recovery, are crucial for the deplo...
research
10/02/2019

Deep Reinforcement Learning for Single-Shot Diagnosis and Adaptation in Damaged Robots

Robotics has proved to be an indispensable tool in many industrial as we...
research
03/24/2021

Behavior coordination for self-adaptive robots using constraint-based configuration

Autonomous robots may be able to adapt their behavior in response to cha...
research
03/04/2023

Technical Report on: Tripedal Dynamic Gaits for a Quadruped Robot

A vast number of applications for legged robots entail tasks in complex,...

Please sign up or login with your details

Forgot password? Click here to reset