This paper introduces the Passive Transformable Omni-Ball (PTOB), an advanced omnidirectional wheel engineered to enhance step-climbing performance, incorporate built-in actuators, diminish vibrations, and fortify structural integrity. By modifying the omni-ball’s structure from two to three segments, we have achieved improved in-wheel actuation and a reduction in vibrational feedback. Additionally, we have implemented a sliding mechanism in the follower wheels to boost the wheel’s step-climbing abilities. A prototype with a 127 mm diameter PTOB was constructed, which confirmed its functionality for omnidirectional movement and internal actuation. Compared to a traditional omni-wheel, the PTOB demonstrated a comparable level of vibration while offering superior capabilities. Extensive testing in varied settings showed that the PTOB can adeptly handle step obstacles up to 45 mm, equivalent to 35 % of the wheel’s diameter, in both the forward and lateral directions. The PTOB showcased robust construction and proved to be versatile in navigating through environments with diverse obstacles.

This paper presents a stochastic/robust nonlinear model predictive control (NMPC) to enhance the robustness of model-based legged locomotion against contact uncertainties. We integrate the contact uncertainties into the covariance propagation of stochastic/robust NMPC framework by lever-aging the guard saltation matrix and an extended Kalman filter-like covariance update. We achieve fast stochastic/robust NMPC computation by utilizing the zero-order algorithm with additional improvements in computational efficiency concerning the feedback gains. We conducted numerical experiments and demonstrate that the proposed method can accurately forecast future state covariance and generate trajectories that satisfies constraints even in the presence of the contact uncertainties. Hardware experiments on the perceptive locomotion of a wheeled-legged robot were also carried out, validating the feasibility of the proposed method in a real-world system with limited on-board computation.

The utilization of mobile robots equipped with multiple light detection and ranging (LiDAR) sensors, capable of perceiving their surroundings, is on the rise due to the miniaturization and cost reduction of LiDAR technology. This paper introduces a target-less extrinsic calibration method for multiple LiDARs with non-overlapping fields of view (FoV). The proposed method leverages accumulated point clouds of the floor plane and objects obtained during robot motion. It enables accurate calibration, even in challenging configurations where LiDARs are directed towards the floor plane, which can introduce biased feature values. Additionally, the method incorporates a noise removal module that takes into account the scanning pattern to address bleeding points, which are significant sources of error in point cloud alignment when using high-density LiDARs. Evaluations conducted through simulation demonstrate that the proposed method achieves higher accuracy in extrinsic calibration with two and four LiDARs compared to conventional methods, regardless of the type of objects. Furthermore, experiments conducted using a real mobile robot validate the effectiveness of our proposed noise removal module in precisely eliminating noise compared to conventional methods. The estimated extrinsic parameters successfully contribute to the creation of consistent 3D maps.

To achieve safe legged locomotion, it is crucial to generate motion in real-time considering various constraints in robots and environments. In this study, we propose a lightweight real-time perceptive motion control system for the newly developed six-wheeled-telescopic-legged robot, Tachyon 3. In the proposed method, analytically smoothed constraints including Smooth Separating Axis Theorem (SSAT) as a novel higher order differentiable collision detection for 3D shapes is applied to the Control Barrier Function (CBF). The proposed system integrating the CBF achieves online motion generation in a short control cycle of 1 ms that satisfies joint limitations, environmental collision avoidance and safe convex foothold constraints. The efficiency of SSAT is shown from the collision detection time of 1 µs or less and the CBF constraint computation time for Tachyon 3 of several µs. Furthermore, the effectiveness of the proposed system is verified through the stair-climbing motion, integrating online recognition in a simulation and a real machine.

This paper introduces a quadruped robot, Tachyon, which aims to achieve high payload, robust, and dynamic locomotion on the various terrain with high energy efficiency. Thanks to a novel compact series-parallel elastic actuator (SPEA) on the upper link and a four-bar linkage design in the knee joint for constant vertical foot force, the 41-kg robot can carry more than 20 kg of payloads with dynamic walking. The combination of a robust horizontal CoM stabilizer and SPEA joint torque controller provides low impedance force controllability of the whole-body even when only the knee joint can accurately detect its joint torque. The major performance of Tachyon is demonstrated by carrying a 20-kg rice bag—half of its body weight—and climbing stairs with dynamic locomotion. When the robot climbs the stairs, the SPEA parallel spring improves energy efficiency by 16% and is also effective for various other gaits. The robustness of the robot is also shown by its high flexibility and fall avoidance capability when an unknown disturbance of 400 N or more is applied.

In this paper, we propose control system which supports unicycle operation for human's skill up. Therefore, the unicycle operation analysis method is proposed first, and it is shown usefulness by experiment. The element used for analysis are rider's CP (Center of Pressure) and MBP (Moment Balancing Point) which negates a saddle rotation moment. Using those elements, we propose evaluation method of unicycle rider's operation. Dynamic unicycle simulator is used for supports unicycle operation for human's skill up.