Abstract
The focus of research in biped locomotion has moved toward real-life scenario applications, like walking on uneven terrain, passing through doors, climbing stairs and ladders. As a result, we are witnessing significant advances in the locomotion of biped robots, enabling them to move in hazardous environments while simultaneously accomplishing complex manipulation tasks. Yet, considering walking in an unknown environment, the efficiency of humanoid robots is still far from being comparable with the human. Currently, bipeds are very sensitive to external changes and they have severe constraints for adaptation of walk to conditions from such a complex environment. Promising approaches for efficient generation and realization of walking in a complex environment are based on biological solutions that have been developed for many years of evolution. This work presents one such human-inspired methodology for path planning and realization of biped walk appropriate for motion in a complex unfamiliar environment. Path planning results in calculating clothoid curves that represent well the human-like walking path. The robot walk is realized by the composition of parametric motion primitives. Such an approach enables on-line modification of planned path and walk parameters at any moment, instantly. To establish the relationship between high-level path planner and the low-level joint motion realization, we had to find a way to extract the parameters of the clothoid paths that can be linked with the parameters of the walk and consequently to motion primitive parameters. This enabled the robot to adopt its walking for avoiding the obstacles and for a smooth transition between different paths. In this paper we provide a complete framework that integrates the following components: (i) bio-inspired online path planning, (ii) path-dependent automatic calculation of high-level gait parameters (step length, walking speed, direction, and the height of the foot sole), and (iii) automatic calculation of low-level joint movements and corresponding control terms (driving motor voltage) through the adaptation of motion primitives which realize walking pattern and preserves the dynamic balance of the robot.
Highlights
We are witnessing that jobs which were in the past exclusively handled by humans, spanning from the care of patients in hospitals to playing musical instruments, are possible to be carried out by robots
The contribution of this work is the framework for online human-like path planning and walking that integrates (i) the human-inspired path planning algorithm, (ii) the link between the parameters of the walk and the reconfigurable adaptive motion primitives (RAMPs) parameters for defining joints motion, and (iii) the dynamic balance controller that compensates for disturbances and ensures the dynamic balance of the robot
Since motion primitives do not consider the dynamic balance of the system, the third block is introducing the corrections of desired joint velocities taking into consideration current position of Zero Moment Point (ZMP) and projection of the center of mass to ensure the preservation of dynamic balance
Summary
We are witnessing that jobs which were in the past exclusively handled by humans, spanning from the care of patients in hospitals to playing musical instruments, are possible to be carried out by robots. The contribution of this work is the framework for online human-like path planning and walking that integrates (i) the human-inspired path planning algorithm, (ii) the link between the parameters of the walk and the RAMP parameters for defining joints motion, and (iii) the dynamic balance controller that compensates for disturbances and ensures the dynamic balance of the robot. Planners to generate the safe path toward the goal (Kuindersma et al, 2016), usually followed by the foot placement algorithm and precise realization of generated trajectories Other approaches, such as Zaytsev et al (2015), propose that the planner should focus on local tasks, and plan only a few steps ahead. The coefficient b ensures the smooth transition in intensity and direction of the heel velocity
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