In context
As intelligent warehousing expands, demand grows for mobile robots that can navigate complex environments and perform human-centric tasks. Bipedal robots, with their human-like morphology, offer unique potential for such settings, yet their design often relies on empirical methods lacking integrated control and structural optimization.
What was reported
Researchers from Shanghai Jiao Tong University proposed a bipedal robot design and control method based on joint coordinated control. They combined time-based and event-triggered detection for stable ground contact, and fused joint encoder and IMU data via a Kalman filter for accurate state estimation. Simulations showed position errors below 1% over a 10 m range, outperforming time-based methods.
A joint coordinated controller was developed with progressive gait and torso tilt control mechanisms, enabling smooth standing-to-walking transitions within 5 seconds. The controller uses a task-priority framework, with balance tasks prioritized for bipedal stability.
Through simulation, a cooperatively driven hip joint was designed, reducing the maximum torque requirement for the hip yaw motor by 40%. A physical prototype was built and tested, validating the approach's effectiveness and practical potential.
Why it mattered
This work demonstrates a closed-loop framework integrating control algorithms, simulation, and structural design, offering a systematic path to optimize bipedal robots for real-world applications like warehousing and service robotics.
Compared to single time-based detection methods, the proposed approach exhibits better stability and achieves position estimation errors of less than 1% within a 10 m range.
Source: 《机器人》期刊 (robot.sia.cn) · Published 2025-08-19 · “基于关节协同控制的仿人双足机器人设计及优化”