All posts by Linda Seward, NCCR Robotics

The field of drone delivery is currently a big topic in robotics. However, the reason that your internet shopping doesn’t yet arrive via drone is that current flying robots can prove a safety risk to people and are difficult to transport and store.

A team from the Floreano Lab, NCCR Robotics and EPFL present a new type of cargo drone that is inspired by origami, is lightweight and easily manoeuvrable and uses a foldaway cage to ensure safety and transportability.

A foldable protective cage sits around a multicopter and around the package to be carried, shielding spinning propellers and ensuring safety of all people around it. When the folding cage is opened in order to either load or unload the drone, a safety mechanism ensures that the engine is cut off, meaning that safety is ensured, even with completely untrained users.

But where this drone takes a step forward is in the folding cage, ensuring that it can be easily stowed away and transported. The team took inspiration from the origami folding shelters that have been developed for space exploration and adapted them to create a chinese lantern shape, and instead of using paper, a skeletal structure is created using carbon fibre tubes and 3D printed flexible joints. The cage is opened and closed using a joint mechanism on the top and bottom and pushing apart the resulting gap – in fact, both opening and closing of the cage and be performed in just 1.2 seconds.

By adding such a cage to a multicopter, the team ensure safety for those who come into contact with the drone. The drone can be caught while it’s flying, meaning that it can deliver to people caught in places where landing is hard or even impossible, such as a collapsed building during search and rescue missions, where first aid, medication, water or food may need to be delivered quickly.

Currently, the drone is able to carry 0.5 kg cargo for 2 km, and any visitors to EPFL over this summer would have noticed it being used to transport small items across campus 150 times, but it is hoped that by scaling, it may be able to carry as much as 2 kg over 15 km, a weight and distance that would allow for longer distance deliveries.

Reference:
P.M. Kornatowski, S. Mintchev, and D. Floreano, “An origami-inspired cargo drone”, in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017.

Recent advances in soft robotics have seen the development of soft pneumatic actuators (SPAs) to ensure that all parts of the robot are soft, including the functional parts. These SPAs have traditionally used increased pressure in parts of the actuator to initiate movement, but today a team from NCCR Robotics and RRL, EPFL publish a new kind of SPA, one that uses vacuum, in ScienceRobotics.

The new vacuum-powered Soft Pneumatic Actuator (V-SPA) is soft, lightweight and very easy to fabricate. By using foam and coating it with layers of silicone-rubber, the team have created an actuator that can be made using off the shelf parts without the need for molds – in fact, it takes just two hours to manufacture the V-SPA.

Once produced, the actuators were combined into plug-and-play “V-SPA Modules” which created a simplified design of soft pneumatic robots with many degrees of freedom. In fact, the team created reconfigurable, modular robots using these modules, where every function of the robot was powered by a single shared vacuum source, enabling many different types of capabilities, such as multiple forms of ground locomotion, vertical climbing, object manipulation and stiffness changing.

To test the new modular robot, the team added a suction arm which used the vacuum pump to pick up and move a series of objects, a task that was completed by turning on suction when an object should be carried and allowing the arm to refill with air when the object should be released. Further validation came through attaching suction cups to the robot and using it to climb up a vertical window and using the robot to walk using a number of different gaits (either through use of waves, like a snake, or rolling).

By creating a soft, lightweight actuator that can move in any direction the team hope to enable a new generation of truly soft, compliant robots that can interact safely with the humans that use them.

Reference

M. A. Robertson and J. Paik, “New soft robots really suck: vacuum powered systems empower diverse capabilities,” Science Robotics. doi/10.1126/scirobotics.aan6357

Using Brain Computer Interfaces (BCI) as a way to give people with locked-in syndrome back reliable communication and control capabilities has long been a futuristic trope of medical dramas and sci-fi. A team from NCCR Robotics and CNBI, EPFL have recently published a paper detailing work as a step towards taking this technique into everyday lives of those affected by extreme paralysis.

BCIs measure brainwaves using sensors placed outside of the head. With careful training and calibration, these brainwaves can be used to understand the intention of the person they are recorded from. However, one of the challenges of using BCIs in everyday life is the variation in the BCI performance over time. This issue is particularly important for motor-restricted end-users, as they usually suffer from even higher fluctuations of their brain signals and resulting performance. One approach to tackle this issue is to use shared control approaches for BCI, which has so far been mostly based on predefined settings, providing a fixed level of assistance to the user.

The team tackled the issue of performance variation by developing a system capable of dynamically matching the user’s evolving capabilities with the appropriate level of assistance. The key element of this adaptive shared control framework is to incorporate the user’s brain state and signal reliability while the user is trying to deliver a BCI command.

The team tested their novel strategy with one person with incomplete locked-in syndrome, multiple times over the course of a year. The person was asked to imagine moving the right hand to trigger a “right command”, and the left hand for a “left command” to control an avatar in a computer game. They demonstrated how adaptive shared control can exploit an estimation of the BCI performance (in terms of command delivery time) to adjust online the level of assistance in a BCI game by regulating its speed. Remarkably, the results exhibited a stable performance over several months without recalibration of the BCI classifier or the performance estimator.

This work marks the first time that this design has been successfully tested with an end-user with incomplete locked-in syndrome and successfully replicates the results of earlier tests with able bodied subjects.

Reference:

S. Saeedi, R. Chavarriage and J. del R. Millán, “Long-Term Stable Control of Motor-Imagery BCI by a Locked-In User Through Adaptive Assistance,” IEEE Transactions on neural systems and rehabilitation engineering,” Vol. 25, no. 4, 380-391.

When training to regain movement after stroke or spinal cord injury (SCI), patients must once again learn how to keep their balance during walking movements. Current clinical methods support the weight of the patient during movement, while setting the body off balance. This means that when patients are ready to walk without mechanical assistance, it can be hard to re-train the body to balance against gravity. This is the issue addressed in a recent paper published in Science Translational Medicine by a team lead by Courtine-Lab, and featuring Ijspeert Lab, NCCR Robotics and EPFL.

During walking, a combination of forces move the human body forward. In fact, the interaction of feet with the ground creates the majority of forward propulsion, but with every step, multiple muscles in the body are engaged to maintain movement and prevent falls. In order to fully regain the ability to walk, patients must develop both the muscles and the neural pathways required in these movements.

During partial body weight-supported gait therapy (whereby a patient trains on a treadmill while a robotic support system prevents them from falling), a patient is merely lifted upwards, with no support for forward or sideways movements, massively altering how the person within the support system moves. In fact, those within the training system use shorter steps, slower movements and less body rotation than the same people tested walking unaided.

In an effort to reduce these limitations of current therapy methods, the team developed a multi-directional gravity assist mechanism, meaning that the system supports patients not only in remaining upright, but also in moving forwards. This individually tailored support allows patients to walk in a natural and comfortable way, training the body to counterbalance against gravity and repositioning the torso in a natural position for walking.

The team developed a system, RYSEN, which allows patients to operate within a wide area, and in a range of activities, from standing and walking to walking along a slalom or horizontal ladder light projected onto the floor. They developed an algorithm to take measurements of how the patient is walking, and update the support given to them as they complete their training. The team found that all patients required the system to be tailored to them before use, but that by configuring the upward and forward forces applied during training, almost all subjects experienced significant improvements in movement with even small upward and forward forces on their torso. In fact, patients who experienced paralysis after SCI and stroke, found that by using the system, they were able to walk and thus begin to rebuild muscles and neurological pathways.

This work exists within a larger framework at NCCR Robotics, whereby researchers are using gravity-assisted technologies to play a key role in clinical trials on electrical spinal cord stimulation with the ultimate aim of creating technologies that will improve rehabilitation after spinal cord injury and stroke.

Reference:
Mignardot, J.-B., Le Goff, C. G., van den Brand, R., Capogrosso, M., Fumeaux, N., Vallery, H., Anil, S., Lanini, J., Fodor, I., Eberle, G., Ijspeert, A., Schurch, B., Curt, A., Carda, S., Bloch, J., von Zitzewitz, J. and Courtine, G., “A multidirectional gravity-assist algorithm that enhances locomotor control in patients with stroke or spinal cord injury“, Science Translational Medicine, 2017.

Image: EPFL

Prof. Pierre Dillenbourg and the team from the Computer-Human Interaction in Learning and Instruction (CHILI) Lab, explain how they are building robots to use in the classrooms of tomorrow. It is CHILI’s goal to deeply integrate Human-Computer Interaction (HCI) and learning sciences, especially in addressing practical problems in learning, teaching, and instruction.

If you enjoyed this ‘meet the lab’ video, you can also watch another in the NCCR Robotics series below:

• Meet the labs of NCCR Robotics: Paik Lab
• Meet the labs of NCCR Robotics: Auke Ijspeert and BioRob

The fields of modular and origami robotics have become increasingly popular in recent years, with both approaches presenting particular benefits, as well as limitations, to the end user. Christoph Belke and Jamie Paik from RRL, EPFL and NCCR Robotics have recently proposed an elegant new solution that integrates both types of robotics in order to overcome their individual limitations: Mori, a modular origami robot.

Mori is the first example of a robot that combines the concepts behind both origami robots and reconfigurable, modular robots. Origami robotics utilises folding of thin structures to produce single robots that can change their shape, while modular robotics uses large numbers of individual entities to reconfigure the overall shape and address diverse tasks. Origami robots are compact and light-weight but have functional restrictions related to the size and shape of the sheet and how many folds can be created. By contrast, modular robots are more flexible when it comes to shape and configuration, but they are generally bulky and complex.

Mori, an origami robot that is modular, merges the benefits of these two approaches and eliminates some of their drawbacks. The presented prototype has the quasi-2D profile of an origami robot (meaning that it is very thin) and the flexibility of a modular robot. By developing a small and symmetrical coupling mechanism with a rotating pivot that provides actuation, each module can be attached to another in any formation. Once connected, the modules can fold up into any desirable shape.

The individual modules have a triangular structure with dimensions of just 6 mm in thickness, 70 mm in width and 26 g in weight. Contained within this slender structure are actuators, sensors and an on-board controller. This means that the only external input required for full functionality is a power source. The researchers at EPFL have thereby managed to create a robot that has the thin structure of an origami robot as well as the functional flexibility of a modular system.

The prototype presents a highly adaptive modular robot and has been tested in three scenarios that demonstrate the system’s flexibility. Firstly, the robots are assembled into a reconfigurable surface, which changes its shape according to the user’s input. Secondly, a single module is manoeuvred through a small gap, using rubber rings embedded into the rotating pivot as wheels, and assembled on the other side into a container. Thirdly the robot is coupled with feedback from an external camera, allowing the system to manipulate objects with closed-loop control.

With Mori, the researchers have created the first robotic system that can represent reconfigurable surfaces of any size in three dimensions by using quasi-2D modules. The system’s design is adaptable to whatever task required, be that modulating its shape to repair damage to a structure in space, moulding to a limb weakened after injury in order to provide selective support or reconfiguring user interfaces, such as changing a table’s surface to represent geographical data. The opportunities are truly endless.

Reference

Christoph H. Belke and Jamie Paik, “Mori: A Modular Origami Robot“, IEEE/ASME Transactions on Mechatronics, doi:10.1109/TMECH.2017.2697310