The PhysicsGen system, developed by MIT researchers, helps robots handle items in homes and factories by tailoring training data to a particular machine.
In order to advance the convenience of data collection for humanoid robots, we refer to other solutions to do the adaptation development and open source.
The collaboration between AI and robotics enables robots to implement tasks more effectively and handle complications previously beyond their capacities.
In this episode, we explore two cutting-edge environmental robots developed by ETH Zurich students: MONKEE, a tree-climbing robot for canopy research, and ReefRanger, an autonomous underwater robot that feeds and monitors corals.
Utility robots can't always count on GNSS, especially in dynamic, busy environments like cities or industrial settings. By combining data from multiple sensors, Fixposition shows how sensor fusion can help robots stay on track and work reliably in the real world.
By combining high-precision sensors with sophisticated algorithms, TDK's 6-axis IMU sets a new standard for motion control in the field of service robotics.
Segments of daily training for robots driven by reinforcement learning.
Multiple tests done in advance for friendly service humans.
The training includes some extreme tests, please do not imitate!
A robotic hand developed at EPFL can pick up 24 different objects with human-like movements that emerge spontaneously, thanks to compliant materials and structures rather than programming.