Human Inspired Push Recovery for Locomotive Robots

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Informatics

Abstract

Legged robots share a similar morphology to that of humans; we can exploit this fact to improve robotic control and bring it closer to human level control in walking, manipulation and dynamic body control.
My research focuses on finding ways to first observe salient aspects of human motion, then to analyse it to attempt to extract the underlying principles, convert the extracted rules to a controller for humanoid robots then evaluate the results. This approach gives us an insight into an evolutionary history full of tried and tested solutions to real world interactions and could lead to significant improvements in robotics.

Planned Impact

The Centre will have immediate short-term impacts on people skills and pipeline, alongside advances in scientific knowledge and techniques. However, with the strength of the program's training emphasis on innovation and social/societal challenges we also target longer term economic and societal benefits.
People: Centre graduates will be grounded in fundamental RAS topics and acquire advanced specialist scientific knowledge of crucial interaction themes. They will be skilled at teamwork, with a broader appreciation of RAS ethical issues. They will have international contacts and experience, with public presentation experience. Most importantly, they will be Innovation Ready - skilled in the principles of how technical and commercial disruption occurs, understanding how finance and organization realize new products and services in startup, SME and corporate situations. Their economic impact will be as industrial leaders of the future, foundational in realizing new products and services. This impact will be accelerated by our #Cauldron training programme in the interlinked areas of Scientific Cohesion, Research and Creativity Skills, Social and Societal Challenges, and programmed engagements and activities with our User Partners who shape the Centre's direction.
Science: The Centre will realize scientific advances, e.g. greater understanding of AI vs biomimetic approaches to persistent autonomy, advanced empathetic multimodal interaction between people and machines in smart spaces, advanced robotic micro-sensing and computing in soft embodiments, adaptive compliant actuation at a multitude of scales and form factors, semantic understanding of environments from noisy sensor data and more. Not only the advances, but also the research methods and practice to achieve them will be realized, e.g. hardware-in-the-loop architectures for re-usability and easy, low cost experimentation. The impact of these advances will be enhanced by strongly supported opportunities for dissemination, including conference presentations and publications (and training in presentation and writing skills), reciprocal secondments with Associate Research Partners, international student robot competitions, public outreach activities, CDT hosted international researcher visitors and workshops.
Society: Robotic and autonomous systems decrease cost and risk, increasing productivity while removing human operators from the 'dull, dirty and dangerous' tasks across the industries of our User Partners. Centre graduates and technology will contribute to maintaining UK business competitiveness and exports in this emerging Euro15.5Billion market, whilst improving quality of life for example a) more interesting (and prestigious) day-to-day employment for workers, b) assisted healthcare for an ageing population (including the Centre Directors), and c) greater awareness of environmental impacts and changes leading to policy and legislation.

Publications

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Description Balancing is a tricky task for robots and when we design controllers to make robots balance, they can encounter many difficulties. This project looked a what we can learn by looking at humans and designing controllers based on their behaviour. This work found that humans use 4 distinct methods for balancing when they are pushed and that we can determine a relationship between these strategies. We can also show when these methods will be used based on how hard a person is pushed. We took this information and applied it to a simple robot model, which can now also produce these same actions when pushed over. This is a change from other methods which used these actions is more simplistic or incomplete ways.
Exploitation Route The controller which was output by this project can be applied to humanoid robotics to prevent it from falling over. This would require integration with an existing robot architecture.
Sectors Aerospace, Defence and Marine,Electronics,Other