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| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | Queen Mary University of London |
| Country | United Kingdom |
| Start Date | Sep 30, 2021 |
| End Date | Dec 31, 2025 |
| Duration | 1,553 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2598257 |
With the increasing dependence on automation in virtually all parts of industry, the need for intelligent machines that can safely navigate through different terrains and environments is now more pronounced than ever. At present, one of the major difficulties surrounding soft robotics is the lack of controlled mobility. Getting soft robots to walk in a controlled way in different environments without depending on rigid limbs is a difficult challenge to overcome and requires further research.
Most walking robots such as Spot by Boston Dynamics are made from rigid material. Their success in being able to walk as well as they do is dependent on heavy computer resources which are responsible for controlling how they move. Even while being armed with such computer power, Spot is still quite limited in the variety of places it can walk in.
For example, according to the user's manual: it is not able to walk in wet conditions or in any situation which requires it needs to climb or descend more than 30o inclines. To put this into perspective: this is far less than the maximum angle of 42o allowed by the British Building Regulations for domestic staircases.
Nature, on the other hand, has had this problem solved for millions of years. Soft robots which have attempted to capture some of nature's wisdom in this regard have already shown to be useful in a variety of highly delicate situations including surgery, rehabilitation, underwater exploration and even disaster scenarios. This project will develop on work done previously with the ambition of making a robot that can walk on four inflatable legs, similar to, for example: an octopus' limbs.
Analysing relevant literature and also shows that there is great support of the hypothesis that inflatable limbs similar to biological legs will be more capable of adapting to their environment without needing massive computational power. As of this writing, no such robot exists; which highlights the importance of the proposed research.
AIMS/OBJECTIVES Aims: 1. To manufacture four soft legs that are made of inflatable material
2. To build a soft (or rigid) frame that can hold all four legs, as well as the hardware needed to power and control the way the legs move
3. To use pneumatic technology for controlling the pressure in the legs, and getting them to walk using changes in pressure Objectives:
The first step is to create a single inflatable leg design will be informed by previous work in the literature. Once the this is made, it will be tested based on how well it can bend using air pressure. The next step will then be to make a frame (the robot's body) which will be able to hold four of these legs and control how they move based on increasing/decreasing air pressure.
Finally, the robot's performance will be tested based on how well it can walk in different environments without relying on rigid limbs or massive amounts of computer power. METHODOLOGY
The main line of research will be based on designing a fully inflatable leg that can bend based on the amount of pressure inside. This will require knowledge to be drawn from a variety of different fields in the physical sciences. To successfully make the inflatable limb, new research will need to be conducted in the field of controlled air pressurization technology so that the robot does not depend on an external air compressor.
This will all need to be based on a robust network of sensors. The application of such sensors to the proposed robot will also require new research in order to be successfully implemented. EPSRC ALIGNMENT
This is a broad subject and is expected to align with the following EPSRC themes, according to https://epsrc.ukri.org/research/ourportfolio/researchareas/: Artificial intelligence technologies Control engineering Electrical motors and drives/electromagnetics Engineering design Image and vision computing
Robotics Sensors and instrumentation Software engineering Synthetic biology
Queen Mary University of London
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