Electric motors are widely used in robots but waste energy in many applications. This inefficiency leads to short battery life and hinders the adoption of new robotic technologies ranging from humanoids to exoskeletons.
Stanford researchers have invented an efficient rotary actuator that recycles elastic energy by engaging and disengaging springs using concentric electroadhesive clutches.
Researchers at Stanford University have developed a multilayered immiscible polymer system capable of autonomously realigning its layers to enhance the healing process after damage.
Stanford inventors have created an audio-visual system with a radiotransparent screen provides a means for communication and visual distractions during procedures such as radiation therapy and radiation imaging.
The Follmer group has designed a soft jamming brake and artificial muscle (SJBAM) actuator for improved muscle static and dynamic response along with expanded brake bandwidth.
Stanford researchers have developed a novel method (LISA) for enabling artificial agents / robots to follow natural language instructions in complex environments.
Stanford researchers have developed a method to form orthogonal overlapping joints at the 4 corners of the starting square. In order to have constant height of each beam, inserts in the beams between the joints will be required.
Researchers at Stanford have reported the first high energy density shape memory polymer based on the formation of strain-induced supramolecular nanostructures, which immobilize stretched chains to store entropic energy.
Stanford inventors have developed a mechanical differential that is cable-actuated for controlling a 2 degree-of-freedom (DoF) of mobility in a robotic joint.
One of the largest challenges for soft robotics is obtaining adequate feedback control while forming dexterous movements. Here Stanford researchers have developed a patterning technique using a UV laser on metalized plastic film.
Inspired by the "last inch" problem in robotic manipulation, the Kennedy group at Stanford has developed a tactile sensor and calibration method for machine-learning-based robotic manipulation.