Jul 29, 2026 02:21 AM
https://www.eurekalert.org/news-releases/1137936
INTRO: A new method developed by MIT researchers makes robots better at thinking ahead while they are acting, leading to smoother motions and quicker reactions. This technique enables the artificial intelligence model that plans a robot’s motion to forecast its future position. The model uses this prediction to seamlessly transition current movements into the next actions.
Many existing methods cause a robot to stop and think about what it needs to do next, leading to slow and jerky motions. By basing its calculations on the future state of the robot, rather than its current position, the MIT method helps robots operate much faster.
Importantly, the technique does not add any computational overhead to the planning process and can be applied to varied robotic hardware.
This new method doubled the speed of robots performing activities like pick-and-place tasks, while significantly reducing lag time between motions. It also boosted the performance of robotic arms in highly dynamic activities, such as playing table tennis and Whack-a-Mole.
The system could be especially useful for robots that perform fast and agile maneuvers in challenging real-world environments, like emergency response or search-and-rescue. It could also allow robots to react more quickly when recovering from mistakes.
“This work sets up a good foundation for efficient, fast, accelerated, and low-cost robotics applications. We look forward to expanding our work into the latest world action models, so it has even stronger capabilities as we keep pushing to make physical AI faster,” says Song Han, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), member of the Research Laboratory of Electronics, and lead author of a paperon this method.
Han is joined on the paper by co-lead authors Jiaming Tang, an MIT EECS graduate student, and Yufei Sun, a student at Tsinghua University; as well as others at Nvidia, the University of California at Berkeley, the University of California at San Diego, and Caltech. The research will be presented at the Intelligent Robots and Systems Conference... (MORE - no ads)
INTRO: A new method developed by MIT researchers makes robots better at thinking ahead while they are acting, leading to smoother motions and quicker reactions. This technique enables the artificial intelligence model that plans a robot’s motion to forecast its future position. The model uses this prediction to seamlessly transition current movements into the next actions.
Many existing methods cause a robot to stop and think about what it needs to do next, leading to slow and jerky motions. By basing its calculations on the future state of the robot, rather than its current position, the MIT method helps robots operate much faster.
Importantly, the technique does not add any computational overhead to the planning process and can be applied to varied robotic hardware.
This new method doubled the speed of robots performing activities like pick-and-place tasks, while significantly reducing lag time between motions. It also boosted the performance of robotic arms in highly dynamic activities, such as playing table tennis and Whack-a-Mole.
The system could be especially useful for robots that perform fast and agile maneuvers in challenging real-world environments, like emergency response or search-and-rescue. It could also allow robots to react more quickly when recovering from mistakes.
“This work sets up a good foundation for efficient, fast, accelerated, and low-cost robotics applications. We look forward to expanding our work into the latest world action models, so it has even stronger capabilities as we keep pushing to make physical AI faster,” says Song Han, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), member of the Research Laboratory of Electronics, and lead author of a paperon this method.
Han is joined on the paper by co-lead authors Jiaming Tang, an MIT EECS graduate student, and Yufei Sun, a student at Tsinghua University; as well as others at Nvidia, the University of California at Berkeley, the University of California at San Diego, and Caltech. The research will be presented at the Intelligent Robots and Systems Conference... (MORE - no ads)