International Journal of Humanoid Robotics

Robot suits can amplify human power, mobility, and height. A giant humanoid mobility robot-Method II was designed using the concept of battle robot suit, AMP in the movie Avatar. The operator aboard Method II is a giant robot that can expand its movement to five times the human muscle strength and 2.5 times the height. The robot suit-type controller can move in synchronization with the movement of both arms and control fingers to collaborate with various tasks. However, there are critical challenges, such as battery weight and duration inefficiency, control complexity, network stability, and difficulties in failure or repair work. This study develops and operates the world’s largest humanoid mobility robot without support fixture up to now, and presents its five future research challenges.

In this paper, we propose a computationally fast method of sampling-based global path planning for humanoids under Manifold Constraints such as closed kinematic chains and Volume-Reducing Constraints such as collision avoidance. In multi-contact and whole-body manipulation of humanoids, narrow collision-free space causes path planning to take a long computation time (narrow corridor problem). In previous research of constrained planning, Manifold Constraints are locally approximated by tangent plane, and steering motions along Manifold Constraints are found efficiently by projection or continuation methods. In this paper, we applied constrained planning algorithms to collision avoidance. Since tangent plane cannot approximate Volume-Reducing Constraints, we adopted convex polytope instead of tangent plane. Both Manifold Constraints and Volume-Reducing Constraints are locally approximated by convex polytope with linear equality and inequality constraints, and steering motions inside the convex polytope are found efficiently by the SQP-based prioritized inverse kinematics. We developed CP-KPIECE (Convex Polytope approximation-based KPIECE) with this approach. Benchmarks using the humanoid JAXON proved the effectiveness of our approach for fast path planning in narrow collision-free space of humanoids.

Humans can perform stable motion with a sense of stability that involves identifying their center of gravity point with plantar sensory system. By contrast, the stability of a humanoid robot is inferior to that of a human. If the sense of stability of a humanoid robot is presented to a human who operates the robot in real time, the operator can control the robot more stably. However, studies wherein humans recognize the projected center of gravity point with a plantar haptic display are lacking. In this study, we investigated the possibility of estimating the projected center of gravity point of a small humanoid robot from only the foot force information. We propose a plantar haptic display to reproduce the foot reaction force on four points of a single sole as large as the force during human running. We conducted an experiment to verify the estimated center of gravity point using the foot reaction forces of a small robot with and without scaling by a weight ratio between an operator and the robot. The results indicated that it is difficult to estimate the projected center of gravity point without scaling; however, it is possible to estimate the movement of the projected center of gravity point with a maximum error of $\sim 10$ mm with scaling.