Robot specific motion reduces time and energy in construction tasks
Beyond Human-Derived Motion: Exploring Robot-Specific Execution for Construction Humanoids
Robotics
Summary
Construction robots often copy human movements to work with tools built for people. This study shows that if robots use their own types of movements instead of just copying humans exactly, they can do tasks like picking and stacking materials faster and with less effort. The researchers tested this on a large humanoid robot and found it moved more efficiently by changing posture and paths during the task. This suggests robots could work better if allowed to move in ways suited to their own bodies, not just like humans.
What this means in practice
- •For construction robotics teams: Improve robot motion plans by creating robot-specific movements that reduce execution time and energy in material handling tasks.
- •For industrial automation engineers: Design humanoid robots that optimize tasks with motion customized for robot bodies rather than strictly human-like gestures.
Authors
MinJun Chang, Taehyung Kim, Yong K. Cho, Francis Baek
Abstract
Construction productivity has remained a per- sistent challenge, motivating growing interest in humanoid robots that can operate in workspaces and with tools designed for human workers. Realizing this potential requires effective motion control, for which human-derived motion transfer has emerged as a promising approach by capturing and retargeting human demonstrations to humanoid robots. While promising, however, human-derived motion transfer may not fully define how a humanoid should ultimately execute the transferred motion. Once task-relevant motion information has been con- veyed, the humanoid may also exploit its own embodiment through motions that depart from the human demonstration. This study examines whether such Robot-Specific Motion offers an advantage in motion execution efficiency over Human- Derived Motion. On an adult-sized Unitree H1-2, Human- Derived Motion was generated through vision-based capture and retargeting, whereas Robot-Specific Motion used inverse kinematics and minimum-jerk transfers to reach the same targets while departing from the demonstrated posture, as verified using Rapid Upper Limb Assessment (RULA). Across a pick-and-stack sequence representing construction material handling, with four matched motion targets and three trials per condition, Robot-Specific Motion achieved 12.87 s versus 25.03 s in execution time, 0.92 m versus 4.33 m in trajectory length, and 58.7 J versus 247.3 J in two-arm mechanical work. These findings suggest that allowing humanoids to depart from demonstrated human motion may offer additional opportunities for more efficient motion execution, while broader construction tasks are needed to determine whether such differences trans- late into productivity gains.