The words ‘robot’ and ‘robotic’ conjure up images of rigid, unemotional automatons that are as far removed from sensitive, hot-blooded human beings as you can get. But as robots creep increasingly into our everyday lives, one designer is out to change that feeling.
Rob Scharff, a researcher at Delft University of Technology in the Netherlands, has developed a 3-D printed soft robotic limb that responds to a human handshake by squeezing your hand back, mimicking human-to-human interaction.
“Currently, the feedback that robots are able to give humans is underdeveloped as compared to human-human communication,” explains Scharff. “In human-human communication, verbal communication is supported and complemented by body language. Integrating these human-like qualities in robotics can help to make communication with robots more intuitive.”
Scharff’s soft robotics prototype is printed from a flexible material and integrates air chambers in the palm of the robot’s hand, which expand and contract in response to pressure, such as from a human grasp, causing the robot’s fingers to grip either more or less. The fingers and thumb of the hand can be controlled separately and the robot’s wrist rotates in both directions – making the robot all the more human as it does so.
“Qualities [such] as movement and tactility become parameters that designers can play with to design expression,” he adds. “Designing a robot’s expression is no longer limited to making use of the existing actuators [like] screens and speakers, but can be deeply embedded in the design of the robot’s actuators, sensors and body.”
The robotic limb was on show at Dutch Design Week 2015 in October, an annual event to show off the designs of the future. Scharff is looking at developing the technology into custom 3D printed gloves that can help stroke victims learn to grip objects again. Development of soft robotics can have many uses; making hitherto cold, rigid robots seem much softer and human-like holds much promise in the area of prosthetics, care robots, and even industrial grippers where a delicate touch is required. Such developments might go some way to making robots less robotic.
We propose a novel robotic system for physiotherapy and rehabilitation of the upper limb (arm). It will look to address pathologies from post-stroke neuromuscular deficiencies to cerebral palsy in infants.
Our robot is primarily for home use and for patients suffering with loss of motor control. Worldwide, up to 1 billion people suffer from neurological disorders, many of them disabling. It is estimated that in the UAE alone a person suffers a stroke every hour. We could offer these patients a greater chance to have a life that works around their motor disability.
Existing technologies, such as exoskeletons or haptic manipulator, have the proven advantage of enhanced involvement of the patient and, in many cases, of faster and more effective rehabilitation results. They are, however, expensive, and only available on site at few hospitals or specialised clinical centres. Moreover, they are usually rarely used as they require highly-trained staff to be able to deliver the therapy.
With the RE-ACT robot, the patient would be able to benefit from affordable and effective assistive robotic rehabilitation, not only at hospitals but also at home.
The RE-ACT is designed to be a paradigm shift in robotic rehabilitation. Traditional methods of inducing human motion require large and heavy-duty robots, which usually wrap around the limbs causing constraint motion. Our proposed idea will create a more natural and lightweight motion that will not require the user to wear exoskeletons.
The system is implemented with multiple layers of safety to ensure the safety of the patient and it guarantees ease of use and full autonomy that guides the user through the stages of therapy.
We have ensured that the functioning robot is fully autonomous, so that minimal input from the user is needed, thus the robot guides the user in achieving tasks instead of the user commanding the robot. In addition, the robot has machine learning algorithms that enable it to use past data to adapt to the capabilities of the user and to increase or decrease the difficulties of the tasks.
Robots can be surprisingly fragile. A breakdown in a key component can leave even the most advanced and expensive machines disabled or functioning below peak performance.
While the smartest of self-learning machines can adapt to the breakdowns and resume their normal function, this has traditionally been a slow process, as the robots’ programmes work through thousands upon thousands of options. Now though researchers have developed algorithms which speed the learning process, cutting time for adaptation to minutes instead of hours.
Detailed in the journal Nature, researchers have shown how giving some additional guidance to a trial-and-error algorithm can slash the time it takes a robot to figure out how to get back to work. In theory, robots could be taught ‘previous experience’ helping them to eliminate the myriad of bad options from the choices they consider as they adapt to any damage.
Trials of the algorithm with a six-legged hexapod robot showed how a damaged machine could rapidly figure out how it was affected by the damage and find an alternative way to work. If the work continues to be successful it could represent a major step forward in creating adaptable robots at a much lower price point than current levels.