Researchers at the University of Chicago and the Illinois Institute of Technology recently developed Granulobot, a new modular robotic system that can change its physical shape to best navigate different environments.
Because they can go where humans can't, robots are especially uniquely suited for safely working with hazardous nuclear waste. But first, those robots need to become like the humans they are replacing, with arms and fingers that can closely mimic the movements of a person.
Soft robots use pliant materials such as elastomers to interact safely with the human body and other challenging, delicate objects and environments. A team of Rice University researchers has developed an analytical model that can predict the curing time of platinum-catalyzed silicone elastomers as a function of temperature. The model could help reduce energy waste and improve throughput for elastomer-based component manufacturing.
In recent years, roboticists and computer scientists have been trying to develop increasingly efficient methods to teach robots new skills. Many of the methods developed so far, however, require a large amount of training data, such as annotated human demonstrations of how to perform a task.
Researchers at University of Michigan recently developed SKOOTR, a tri-pedal skating robot that can efficiently move around in its surroundings without repeatedly flipping over. This robot, introduced in a paper posted to the preprint server arXiv, was found to be more stable than other three-legged robots, which often exhibit poor stability due to the lack of a fourth leg to better balance their body.
Auke Ijspeert and his team in the BioRobotics Lab (BioRob) in EPFL's School of Engineering had operated their bio-informed robots in natural environments before, but this was more for demonstration purposes than for scientific rigor. Tests of robotic function were usually carried out in the lab, for example, using X-ray videos to compare robotic movements with the animals that inspired their design.
Home robots could assist humans with the completion of various chores and manual tasks, ranging from washing dishes or doing the laundry to cooking, cleaning and tidying up. While many roboticists and computer scientists have tried to improve the skills of home robots in recent years, many of the robots developed so far are still unable to tackle more complex and creative tasks, such as cooking in collaboration with human users.
At the 2024 European Robotics Forum taking place in Rimini, Italy, researchers of Istituto Italiano di Tecnologia (IIT- Italian Institute of Technology) have shown the most recent results from the project SOPHIA: A collaborative robot to guide workers and relieve the burden of overhead tasks such as drilling, wearable robots to support the lifting and carrying of heavy loads physically, and wearable feedback devices to alert users about awkward postures.
If a robot traveling to a destination has just two possible paths, it needs only to compare the routes' travel time and probability of success. But if the robot is traversing a complex environment with many possible paths, choosing the best route amid so much uncertainty can quickly become an intractable problem.
The robot known as ANYmal has, for some time, had no problem coping with the stony terrain of Swiss hiking trails. Now researchers at ETH Zurich have taught this quadrupedal robot some new skills: It is proving rather adept at parkour, a sport based on using athletic maneuvers to smoothly negotiate obstacles in an urban environment, which has become very popular. ANYmal is also proficient at dealing with the tricky terrain commonly found on building sites or in disaster areas.
A new University of Michigan study on how humans and robots work together on tasks with conflicting objectives is the first to demonstrate that trust and team performance improve when the robot actively adapts to the human's strategy.
When lower limb exoskeletons—mechanical structures worn on the leg—do not operate properly, some people adjust quickly while others compensate with their ankle or hip, expending more energy than necessary, according to a new study by University of Michigan researchers.
The perception of softness can be taken for granted, but it plays a crucial role in many actions and interactions—from judging the ripeness of an avocado to conducting a medical exam, or holding the hand of a loved one. But understanding and reproducing softness perception is challenging because it involves so many sensory and cognitive processes.
Robots that can closely imitate the actions and movements of humans in real-time could be incredibly useful, as they could learn to complete everyday tasks in specific ways without having to be extensively pre-programmed on these tasks. While techniques to enable imitation learning considerably improved over the past few years, their performance is often hampered by the lack of correspondence between a robot's body and that of its human user.
Odd things can happen when a wave meets a boundary. In the ocean, tsunami waves that are hardly noticeable in deep water can become quite large at the continental shelf and shore, as the waves slow and their mass moves upward.