Autonomous Robots with Common Sense

This project aims to develop an 'Artificial Physical Awareness' autopilot system for autonomous robots, enabling them to operate safely and effectively despite failures by understanding their limitations.

Subsidie
€ 1.996.040
2024

Projectdetails

Introduction

Autonomous robots such as autonomous vehicles, cars, and drones have the potential to revolutionize the way we work and live. Unfortunately, current autonomous robots do not have ‘common sense’ and may enter a catastrophic condition called loss-of-control after failures. The ultimate goal of this research is to enable a new generation of autonomous robots that are aware of their physical capabilities and limitations, allowing them to act with common sense after failures.

Proposed Solution

To achieve this, I propose a new paradigm in autonomous robot control: ‘Artificial Physical Awareness’ (APA). APA requires accurate real-time knowledge of the time-varying stochastic safe envelope, which is a subset of the state-space inside which safe operations of the autonomous robot can be guaranteed.

Characteristics of the Safe Envelope

The safe envelope is stochastic and time-varying; it contains uncertainties and will shrink after failures, reflecting the reduced post-failure performance of the autonomous robot.

Challenges

Obtaining and utilizing the time-varying stochastic safe envelope in real-time represents a currently unsolved scientific challenge for the following reasons:

  1. The safe envelope cannot be measured directly.
  2. Current safe envelope computation methods are real-time intractable and/or do not take into account uncertainties.
  3. No control methodology exists that allows for time-varying safe-envelope informed balancing of safety and performance.

Multidisciplinary Approach

This multidisciplinary research combines new insights in:

  • Time-varying stochastic state reachability analysis
  • Tipping-point forecasting
  • Bio-inspired envelope sensing and recovery
  • Nonlinear fault-tolerant control

to develop the new APA-autopilot system, which is the main output of this research.

Potential Impact

This research project has the potential to lead to a revolution in autonomous robot design and operations by providing transparent safety and performance bounds, even after failures.

Financiële details & Tijdlijn

Financiële details

Subsidiebedrag€ 1.996.040
Totale projectbegroting€ 1.996.040

Tijdlijn

Startdatum1-7-2024
Einddatum30-6-2029
Subsidiejaar2024

Partners & Locaties

Projectpartners

  • TECHNISCHE UNIVERSITEIT DELFTpenvoerder

Land(en)

Netherlands

Vergelijkbare projecten binnen European Research Council

ERC STG

MANUNKIND: Determinants and Dynamics of Collaborative Exploitation

This project aims to develop a game theoretic framework to analyze the psychological and strategic dynamics of collaborative exploitation, informing policies to combat modern slavery.

€ 1.497.749
ERC STG

Elucidating the phenotypic convergence of proliferation reduction under growth-induced pressure

The UnderPressure project aims to investigate how mechanical constraints from 3D crowding affect cell proliferation and signaling in various organisms, with potential applications in reducing cancer chemoresistance.

€ 1.498.280
ERC STG

Uncovering the mechanisms of action of an antiviral bacterium

This project aims to uncover the mechanisms behind Wolbachia's antiviral protection in insects and develop tools for studying symbiont gene function.

€ 1.500.000
ERC STG

The Ethics of Loneliness and Sociability

This project aims to develop a normative theory of loneliness by analyzing ethical responsibilities of individuals and societies to prevent and alleviate loneliness, establishing a new philosophical sub-field.

€ 1.025.860

Vergelijkbare projecten uit andere regelingen

ERC STG

Intuitive interaction for robots among humans

The INTERACT project aims to enable mobile robots to safely and intuitively interact with humans in complex environments through innovative motion planning and machine learning techniques.

€ 1.499.999
ERC STG

Deep Bayesian Reinforcement Learning -- Unifying Perception, Planning, and Control

Develop an algorithmic framework using deep learning and Bayesian reinforcement learning to enhance robotic manipulation in unstructured environments by effectively managing uncertainty.

€ 1.500.000
ERC STG

Robotic Emulation of Human Failure Comprehension for Vastly Enhanced Resilience through Metacognition

The RECOVER.ME project aims to enable robots in space exploration to autonomously recover from hardware faults using metacognitive awareness and self-programming strategies.

€ 1.499.250
ERC POC

Automated Synthesis of Certifiable Control Software for Autonomous Vehicles

CertiCar aims to develop a reliable, formally correct advanced collision avoidance system to enhance safety and reduce testing time for autonomous vehicle control software.

€ 150.000