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Yang et al. Intell Robot 2024;4(1):107-24 I http://dx.doi.org/10.20517/ir.2024.07 Page 109

Figure 1. The schematic of the human-exoskeleton-walker system. (A) A real exoskeleton robot with a robotic walker; (B) The support joint
and the wheels of the robotic walker shall be controlled to follow the walking of the human-exoskeleton system.

walkers are developed for the energy cost reduction of humans and are not applicable to the HEW system. For
optimization-based approaches, Ding et al. used Bayesian optimization to identify the peak and offset timing
of hip extension assistance that minimizes the energy expenditure of walking with a textile-based wearable
device, causing reduced metabolic cost by 17.4% ± 3.2% compared with walking without the device [15] . Song
and Collins used human-in-the-loop optimization to largely improve self-selected walking speed through an-
[16]
kle exoskeleton assistance, which achieved a reduced metabolic cost by at most 31% . In addition, Lee and
Rosen developed new energy optimization strategies utilizing collision-based ground reaction forces and a dis-
crete Lagrangian to realize the energy recycling of the exoskeleton, achieving a 35% reduction of the normal
walking cost of transport [17] .

Although the BWS-based approach has demonstrated its energy efficiency, it is mostly used to reduce human’s
energy cost and is not applicable to the HEW system. In this paper, we focus on the coordinated energy-
efficient walking assistance of the HEW system, and the human-in-the-loop optimization for the energy con-
sumptionofthehuman-exoskeletonsystemisthekeyresearchtopic. Thekeypointsareasfollows: First,tofind
the optimal supporting force of the robotic walker during walking, which can provide the human-exoskeleton
system with the body weight support to maximize energy efficiency. Second, to generate appropriate joint
angles as the control reference of the wheels to produce a coordinated movement of the robotic walker and the
human-exoskeleton system during walking. However, due to the unknown relationship between the energy ef-
ficiency and the supporting force, it is difficult to calculate the optimal supporting force during walking. In this
paper, a Coordinated Energy-Efficient Control (CEEC) approach is proposed for the HEW system to provide
the coordinated movement of the human-exoskeleton system and the robotic walker and maximize the energy
efficiency of the HEW system. CEEC consists of a model-free Extremum Seeking Control (ESC) algorithm
and a coordinated motion planning approach, which performs real-time seeking of the supporting force and
generation of the joint angles of the wheels. The ESC uses a low-frequency perturbation signal to estimate the
gradient of the cost function, making it more robust to noisy measurements [18] . The main contributions are
summarized as follows:

• The energy efficiency of the HEW system is maximized by the extremum seeking control algorithm in real
time to simultaneously tune the supporting force of the support joint. The optimum of the supporting force
shifts at different conditions, and our algorithm is suitably fast to track these changes, providing real-time
adaptation for different conditions.
• AcoordinatedmotionplanningapproachisproposedfortheHEWsystem,whichperformsthecoordinated