International Journal of Humanoid Robotics

Re-planning of gait trajectory is a crucial ability to compensate for external disturbances. To date, a large number of methods for re-planning footsteps and timing have been proposed. However, robots with the ability to change gait from walking to running or from walking to hopping were never proposed. In this paper, we propose a method for re-planning not only for footsteps and timing but also for the types of gait which consists of walking, running and hopping. The re-planning method of gait type consists of parallel computing and a ranking system with a novel cost function. To validate the method, we conducted push recovery experiments which were pushing in the forward direction when walking on the spot and pushing in the lateral direction when walking in the forward direction. Results of experiments showed that the proposed algorithm effectively compensated for external disturbances by making a gait transition.

This paper introduces a vision-based tactile sensor FingerVision, and explores its usefulness in tactile behaviors. FingerVision consists of a transparent elastic skin marked with dots, and a camera that is easy to fabricate, low cost, and physically robust. Unlike other vision-based tactile sensors, the complete transparency of the FingerVision skin provides multimodal sensation. The modalities sensed by FingerVision include distributions of force and slip, and object information such as distance, location, pose, size, shape, and texture. The slip detection is very sensitive since it is obtained by computer vision directly applied to the output from the FingerVision camera. It provides high-resolution slip detection, which does not depend on the contact force, i.e., it can sense slip of a lightweight object that generates negligible contact force. The tactile behaviors explored in this paper include manipulations that utilize this feature. For example, we demonstrate that grasp adaptation with FingerVision can grasp origami, and other deformable and fragile objects such as vegetables, fruits, and raw eggs.

Due to the remarkable performances of some amputee athletes, the power of their running-specific prostheses came to the fore of the discussions. The aim of our study was to compare non-amputee and amputee sprinting motions resulting from optimization using combinations of eight optimality criteria with either fixed or free average velocity. For the description of the amputee and the non-amputee athlete, we created rigid multi-body system models with 16 degrees of freedom in the sagittal plane. Each sprinting motion is the solution of a specific optimal control problem with periodicity and dynamic constraints. We found realistic human-like sprinting motions for both the non-amputee and the amputee athlete. We compared the optimized solutions to dynamics-reconstructed solutions from motion capture data and determined similarity measures for each of them. The investigation of the amputee athlete’s joint torques and ground reaction forces revealed that the real amputee athlete does not exploit the functionality of his running-specific prosthesis as much as the model. The optimal control problems with free average velocity generated human-like sprinting motions as well. However, for specific objective functions the velocities exceed the fastest measured velocities in human sprinting.