This paper introduces an noval autonomous mobile robot, IOMT, designed for indoor and outdoor multi-terrain environments, with a particular focus on stair-climbing capabilities. The robot features a four-wheel independent drive and steering system (4WID-4WIS), allowing it to maintain high maneuverability on smooth surfaces. Furthermore, based on reducing the complexity of the control, the IOMT addresses the challenges associated with stair climbing by controlling the stable pitch angle, effectively reducing the impact of stairs on the robot's posture, such as the pitch angle minimized to an angle smaller than the inclination of the stairs. The design also incorporates a special mechanism that reduces energy consumption through its worm gear system with self-locking characteristics, and combines steering with shock absorption to simplify both the mechanism complexity. This paper not only briefly proposes a stair climbing strategy for the IOMT, but also explores the impact of various design parameters on the robot pitch angle, ultimately validating the feasibility of the design for the stair climbing ability.

Staircases are a challenging terrain frequently encountered in urban environments. While leg-wheel robots take advantage of having both legged and wheeled modes, their ability to negotiate stairs still requires careful planning. This paper presents a novel approach to developing a stair-climbing behavior for leg-wheel transformable robots. A comprehensive stair-climbing strategy is constructed by analyzing the workspace of the leg-wheel mechanism, considering the position of the robot's center of mass, and accounting for foothold displacement owing to the possible leg-wheel forward rolling motion. This strategy enables the robot to safely navigate stairs using its leg-wheel's appropriate parts. Stability during transitions between steps is ensured, and a well-designed swing trajectory is proposed to minimize slippage and impact. The approach is validated through simulations and further tested experimentally on staircases with treads of 27 cm and risers of 12 cm, as well as staircases with treads of 24 cm and risers of 14 cm. The experimental results demonstrate the effectiveness and robustness of the proposed method.

Accurate estimation of contact forces is crucial for effective control of quadrupedal robots, especially in complex locomotion scenarios. In this paper, we introduce a novel force estimation technique for robots equipped with transformable leg-wheels. Unlike conventional methods that focus on forces at specific contact points, our approach expresses varying contact points through a simplified kinematic model and derives the corresponding Jacobian matrices. This allows us to apply the virtual work method to evaluate contact forces across the entire surface of the leg-wheel, including the tips, sides, and other contact regions. This adaptability is particularly advantageous in hybrid locomotion modes, where different parts of the leg-wheel interact with the terrain. The proposed method is highly efficient, relying solely on motor current and position feedback without the need for additional sensors. We validate our approach through simulations and real-world experiments, demonstrating its accuracy, robustness, and applicability under diverse operational conditions.

The leg-wheel transformable robot has the advantage of smooth, fast, and power-efficient motion on flat terrain and negotiability on rough terrain. This study presents a highly dynamic maneuver of the robot to leap onto a step using its legged form from its original form of wheeled driving, taking full advantage of the rapid switching capabilities of the leg-wheel design of the robot. The robot motion is designed based on a reduced-order model and is planned using an optimization method with multiple constraints. In addition, both position and impedance control strategies are investigated. The proposed strategy is experimentally evaluated. The results show that the robot can leap onto a step higher than itself and then smoothly transition back to the wheeled mode after leaping. The dynamic driving-to-leaping maneuver endows the robot with an alternative and time-efficient approach to negotiate the step obstacles.

The state estimation of legged robots often relies on ground contact detection. However, due to complex mechanisms and other factors, ground contact detection can be challenging to obtain in certain situations. This paper presents a velocity estimation method that combines inertia measurement unit (IMU) and encoders, allowing estimation without using the ground contact state as the a priori. In this paper, the initial estimate derived from IMU integration is refined. Following the computation of velocity and ground contact state probabilities using encoder data, these probabilities are employed to modify particle weights within the particle filter framework. Subsequent resampling ensures that the contact status converges toward the correct result. This paper tests the algorithm through simulations and validates the method with physical experiments, showcasing the feasibility of concurrent ground contact state and velocity estimation.

We propose a limb trajectory planning method that considers both body and limb dynamics in robots, particularly suitable for those with non-trivial limb mass. To simplify the complexity and computation cost of using the full-body dynamics of the limbs, a reduced-order model that can simulate the dynamic characteristics of the original limb is proposed. The performance of the model is experimentally validated using an exemplary single leg-wheel of the leg-wheel transformable robot. The limb trajectory optimization is developed using a genetic algorithm that considers many aspects, including body and limb dynamics, limb workspace, limb motion continuity, body tip-over stability, and power consumption. The performance of the proposed limb trajectory planning strategy is experimentally validated using the same leg-wheel transformable robot, and the results confirm the effectiveness of the strategy.

We report on the model-based development of leaping behavior in a RHex-style hexapod robot. A three-legged model is proposed to analyze the dynamic behavior of leaping, and this serves as a guide for implementing the behavior on the empirical robot. The model has a rigid body and three massless and compliant legs, which have rolling contact with the ground for better modeling the leg behavior of the empirical robot. By investigating the model's behavior, a two-step leaping maneuver is developed. The first step is utilized for adjusting the body pitch, synchronizing the phases of all six legs, and speeding up the body's forward velocity. This provides adequate initial conditions for the second step leaping, which creates a long-distance flight and adequate landing for follow-up running. In addition, we also report on the strategy of stride length regulation. With implementation of the range sensor, the robot can regulate its stride in order to reach a specific and desired position for leaping. The gait transition and initiation of leaping is fully autonomous. The behavioral development is implemented in the RHex-style robot and is evaluated experimentally.

Inspired by the observation that the cockroach changes the tripod gait to other gait to cross the step, we report on the design of the step crossing gait in a RHex-style hexapod robot which enables the robot to cross the step with height more than twice of the leg length. Similar to the cockroach's motion, the gait is composed by two stages: rearing stage to lift the front side of the body, and lifting stage to maneuver the center of mass of the body to pass the edge of the step. The inclinometer is utilized to detect the height of the step during crossing, so the robot can automatically adjust the gait to cross the steps with different heights. The performance of the algorithm is experimentally evaluated.