The system integrates a multimodal fall detection framework combining inertial, proprioceptive, and acoustic sensing, along with an improved stance phase detection algorithm.
Researchers in the US developed bipedal robots with a new design, the HybridLeg platform, to advance reinforcement learning.
Featuring a lantern-shaped, sensorized mechanical cover, these robots can safely handle whole-body contact.
To tackle the inherent instability of humanoids, Univeristy of Illinois’ Kinetic Intelligent Machine LAB (KIMLAB) developed a protective design that mitigates fall impacts and allows autonomous recovery to a standing posture, enabling self-reset after each trial.
Combined with multimodal fall detection and enhanced stance phase tracking, this platform paves the way for robust, long-horizon, real-world reinforcement learning experiments.
Rethinking biped design
A video, shared by KIMLAB, details an innovative untethered bipedal robot featuring a unique “hybrid leg” mechanism.
While traditional humanoid robots typically use serial linkages to mimic human anatomy, this design combines the biological familiarity of serial linkages with the mechanical advantages of parallel linkages, such as higher speeds, lower inertia, and superior payload-to-weight ratios.
The Hybridleg is a parallel linkage mechanism in which each link consists of a serial chain, forming a five-bar closed linkage. The robot utilizes 12 motors for actuation, with a significant design choice to concentrate 10 of them near the pelvis, leaving only 2 at the ankles. This configuration drastically reduces distal mass, which minimizes the negative impact of swing leg dynamics and allows for more accurate physics modeling using reduced-order models like the linear inverted pendulum
As a fully self-contained, untethered platform, the robot houses all necessary components—including a single-board computer, IMU, voltage converter, and LiPo batteries—within its body. The presentation concludes by demonstrating the robot’s capabilities through various walking experiments.
Agile hybrid biped
The large-scale bipedal robot demonstrates how a hybrid mechanical design can push humanoid locomotion toward greater agility, strength, and efficiency. Detailed in a recent paper, the robot is built around the HybridLeg mechanism, a novel approach that combines serial and parallel structures to deliver six degrees of freedom per leg while maintaining low inertia and a large workspace.
The design enables faster motion, higher payload capacity, and improved dynamic performance—key requirements for agile bipedal walking. To further enhance structural rigidity and precision, the latest version of the HybridLeg is fabricated using carbon fiber tubes and high-precision bearings, allowing the structure to support its own weight without sacrificing accuracy.
A pair of HybridLegs is assembled into a full bipedal platform using a custom pelvis design inspired by human biomechanics. The pelvis incorporates a yaw angle offset, similar to the toe-out angle in human feet, to expand the reachable workspace of the feet and improve overall stability. Simulation results detailing workspace and velocity ranges are validated through hardware experiments, confirming close agreement between theory and practice.
The robot stands 1.84 meters tall—taller than the average human—while weighing just 29 kilograms (64 pounds). Despite its size, it can be driven by the same class of servo motors typically used in smaller humanoid robots, highlighting the efficiency of the hybrid mechanism and optimized structural design. The paper provides a detailed explanation of the mechanical architecture, along with full kinematic analysis and analytical solutions.
Performance validation encompasses multi-body dynamics simulations, as well as preliminary hardware experiments, including squatting and in-place walking motions. According to researchers, a simple forward walking demonstration further confirms the feasibility of the approach. Together, these results position the Hybrid Leg-based biped as a promising platform for future research in humanoid locomotion, scalable robot design, and real-world dynamic walking experiments.
The Blueprint
