Terrain adaptation gait algorithm in a hexapod walking robot

This paper presents a central pattern generator (CPG)-based locomotion controller, with a foot trajectory generator and sensor-driven reflex, aiming to increase the adaptability of the hexapod robot walking on uneven terrain. The trajectory generator was used to precisely control the foot trajectories to constrain the leg movement in the workspace. The foot trajectories were further shaped by the sensor information from the proposed sensor-driven reflex, making the hexapod able to pass obstacles of different sizes on uneven terrain. In addition, a novel neck joint was designed to implement the sensor-driven reflex, with an active control mechanism for the climbing of high steps or large obstacles. Finally, a series of simulations and prototype tests were carried out to prove the feasibility of the proposed controller. The results showed that with the integration of the foot trajectory generator, sensor-driven reflex and active neck joint, the hexapod robot can achieve a stronger adaptability to uneven terrain and better performance in walking.

Purpose: Personal mobility vehicles (PMVs) are under active development. Most PMVs are wheel-driven, a mode of transport notable for its efficiency. However, wheeled PMVs tend to have poor mobility against negotiating obstacles. The four-wheeled vehicle RT-Mover PType 3 has been developed featuring wheeled legs capable of leg motion. This allows the PMV to overcome uneven terrains, including a step approached at an angle, which ordinary wheelchairs cannot negotiate. Method: This article discusses a gait algorithm in which a leg executes the necessary leg motion when optionally presented with obstacles on a road. In order to lift a wheel off the ground and perform a leg motion, the support wheels must be moved to support points to ensure that the vehicle remains stable on three wheels. When moving towards the target support point, a wheel may encounter another obstacle, and a response method for this case is also described. Results: To assess the gait algorithm, several configurations of obstacles were used for performance tests with a passenger. The capabilities of the PMV were demonstrated through experiments. Conclusion: We proposed a novel gait algorithm for our PMV and realised the proposed motion pattern for PMV-based negotiating obstacles.Implications for RehabilitationOur single-seat personal mobility vehicle, RT-Mover PType 3 features wheels attached on legs capable of performing leg motion, which allows the vehicle to traverse rough terrains in urban areas.We proposed a gait algorithm for RT-Mover PType 3 consisting of a series of leg motions in response to rough terrain. With this algorithm, the vehicle can traverse not only randomly placed obstacles, but also a step approached at an oblique angle, which conventional powered wheelchairs cannot navigate.Experiments with a passenger demonstrated the effectiveness of the proposed gait algorithm, suggesting that RT-Mover PType 3 can expand the mobility and range of activities of wheelchair users.

Unmanned rescue, observation and/or research vehicles with high terrain adaptability, fast velocity and high reliability to reach difficult rough terrain locations are still demanded, but most vehicles increase rough terrain adapt ability at the expense of low velocity and/or complex mechanisms. We propose a novel vehicle consisting of a very simple blade-type crawler and active antennas with rollers, resembling a wharf roach. This configuration assures stable travelling over uneven terrain at high-speeds, with a very simple and reliable mechanism. This article presents the basic concept, mechanical design of the crawler and the antennas, and the basic motion control strategies. Moreover, we built and tested the first small mechanical prototype named KEIOS-I, and got successful results from experiments on uneven terrain at a high-speed traveling, and also lateral travelling and jumping motions. Future work will also implement roller skating mode using the active antennas equipped with rollers.

In this article, the dynamic equations of a spherical mobile robot, named BYQ-III, are derived by utilizing the Lagrange method. There is no simplification throughout the whole dynamic analysis and the derived dynamic equations can be used for more precise studies of spherical mobile robots' behavior. Considering any possible differentiable function for the terrain's curve, only assuming that the spherical shell will remain in contact with the ground and the elastic effect of the spherical shell is ignored, the effect of the terrain's unevenness is completely described in the dynamic equation evaluation. Although there are complicated and nonlinear relations between the spherical shell and rough terrain, proper choice of generalized coordinates leads to the general closed form dynamic equations of motion, and finally results in the effective reduction of simulation time. But there is no need for the numerical method to solve the complex dynamic equation due to the closed form derivation. In the dynamic equation all variables are highly coupled together and their individual effect cannot be decoupled exactly. From this proposed complete model a simplified model for controller design can be extracted and the proposed model description can give an insight about the performance of different controllers of the spherical robots' motion. Simulations with the same initial conditions on a flat surface and rough terrain show that a rough terrain has a considerable effect on the dynamic behavior of the spherical robots. And as the unevenness of the terrain increases, its effect in the dynamic analysis becomes greater and cannot be neglected.

In this paper, we propose a constructive and robust control design for online stabilization of biped robot dynamic motion, especially walking on rough or uneven terrains. We proposed an online moving ground reference map based on both present and future information, which is obtained via minimizing the error of the footstep, and the error of the position and velocity of the Center of Mass (CoM) of the robot. By applying this reference map, robust CoM trajectories can be generated based on preview control. The dynamic simulation results show that the proposed approach can significantly improve walking stability and minimize the error in tracking the pre-defined trajectory even on uneven terrains. The technique is very general and can be applied to a wide variety of humanoid robots.

In particular the advantages of legged compared to wheeled locomotion arise in unstructured, uneven and rough terrain. Based on the sensor system the behaviour control of LAURON III for walking in rough terrain is presented in this paper. To cope with terrain irregularities local behaviours like collision reaction and searching for ground are realised by an adaptation of the basic leg trajectories. Several global behaviours like the control of the body height and the centre of gravity influence the trajectories of all legs simultaneously.

The constraints faced by visually impaired individuals have spurred various human-created innovations to aid them. One such innovation is employing robots as guides for the blind. Numerous studies have delved into utilizing robots as guides for visually impaired individuals. Nevertheless, these robots still encounter limitations, particularly in navigating rough and uneven terrain. To tackle this issue, there's a necessity for a hexapod robot capable of traversing uneven surfaces more effectively than wheeled robots. The hexapod robot developed in this research is an autonomous robot that employs fuzzy logic as its control method. The resultant hexapod robot has showcased outstanding performance, attaining a 100% success rate in navigating the specified path and demonstrating a reliability of 79.78%.

In this paper, we propose a body mechanism for a legged robot to reduce slippage when moving on an uneven terrain. In the proposed landing mechanism, linear spikes are distributed on the grounding, and they move passively with respect to the road surface shape. This mechanism is aimed to improve the grip performance on an irregular road surface and the movement capability. The developed mechanism is mounted on the body of a four-limbed robot named “WAREC-1.” The robot performs crawling motion over an inclined rough terrain. The crawling includes a motion wherein its legs and torso alternately contact the ground. The experimental results show that the downward sliding of the robot is reduced and that the mechanism contributes to improving the grip performance and movement capability on uneven terrain.

This paper presents a biological inverse kinematics (IK) method and a trajectory tracking approach for a 7-DOF robotic manipulator. The system structure of the manipulator is first designed and its forward kinematics is then derived using its Denavit-Hartenberg (DH) parameters. Based on the DH model, an inverse kinematics method using the combination of particle-swarm optimization (PSO) and real coded genetic algorithm (RGA) is proposed to find the seven joint angles of the manipulator while moving from one point to another, and then a smooth continuous trajectory is planned by connecting several via points. For trajectory tracking, a Jacobian inverse kinematic method along with a P controller and PI speed joint controllers is used to achieve trajectory tracking control with an acceptable accuracy. The effectiveness and merit of the proposed trajectory planning and tracking methods are well exemplified by conducting two simulations.

We describe in detail a novel kinematic simulation of a three-wheeled mo- bile robot moving on extremely uneven terrain. The purpose of this simulation is to test a new concept, called Passive Variable Camber (PVC), for reducing undesir- able wheel slip. PVC adds an extra degree of freedom at each wheel/platform joint, thereby allowing the wheel to tilt laterally. This extra motion allows the vehicle to better adapt to uneven terrain and reduces wheel slip, which is harmful to vehicle efficiency and performance. In order to precisely model the way that three dimensional wheels roll over uneven ground, we adapt concepts developed for modeling dextrous robot manipu- lators. The resulting equations can tell us the instantaneous mobility (number of de- grees of freedom) of the robot/ground system. We also showed a way of specifying joint velocity inputs which are compatible with system constraints. Our modeling technique is adaptable to vehicles of arbitrary number of wheels and joints. Based on our simulation results, PVC has the potential to greatly improve the motion performance of wheeled mobile robots or any wheeled vehicle which moves outdoors on rough terrain by reducing wheel slip.

Nowadays the multi-rotor UAVs are used a lot in military and civilian fields and which are playing an increasingly important role. However, the fixed support frames made of metal or composite material acting as landing gears are widely used on the multi-rotor UAVs, which have shortages and can’t be applied to the landing environment with uneven terrain. So a new kind of terrain-adaptive bionic landing gear is proposed in this article with the function of adapting complex terrains and makes the multi-motor UAVs landing on rough terrain, great slope and step floor. The composition and designing principles of the system are introduced at first. Based on the working process, the design method of one-leg system is detailed described as a basic part, and the kinematic solution of multi-leg system is also based on this through coordinate transform. And through virtual simulation, laboratory debugging and flight test, the feasibility and correctness of the design are shown at last. From the jobs in this article, the terrain-adaptive landing gear can be successfully used on multi-rotor UAVs when landing on some complex terrain through adjusting the orientation of the legs. Compared to the traditional design forms, the design has important engineering application value.

Adaptability to different terrains is crucial for legged robots to perform diverse tasks. This paper proposes a real-time updated control framework that improves the robustness of quadruped robots walking blindly on rough terrain. The proposed framework that considers both stability and kinematics has several advantages: 1) no visual feedback, 2) self-adaptation to unpredictable touchdown position and 3) self-adjustment for unknown rough terrain. The controller tracks the desired robot's CoM (center of mass) postion and posture through optimized distributed ground reaction forces obtained by QP (quadratic programming). By implementation of the proposed method, SIT-Dog robot can achieve stairs climbing and irregular terrrain crossing in the simulation environment.

Soft soles absorb impacts and cast ground unevenness during locomotion on rough terrains. However, they introduce passive degrees of freedom (deformations under the feet) that complexify the tasks of state estimation and overall robot stabilization. We address this problem by developing a control loop that stabilizes humanoid robots when walking with soft soles on flat and uneven terrain. Our closed-loop controller minimizes the errors on the center of mass (COM) and the zero moment point (ZMP) with an admittance control of the feet based on a simple deformation estimator. We demonstrate its effectiveness in real experiments on the HRP-4 humanoid.

In this paper, we address the motion efficiency in autonomous robot exploration with tracked vehicles in rough terrain. Tracked vehicles, along with wheel-driven propulsion systems, are the preferred platform for Unmanned Ground Vehicles (UGVs) in poor terrain conditions. However, these robots have problems with cornering, turning maneuvers or rotation around the central axis. Depending on the coefficient of friction between the tracks and the ground, the total weight and center of mass tracked vehicles produce higher slip, purely accurate and reliable pose estimation. To improve the direction of motion and the prediction of the resulting track forces and odometry calculation for tracked vehicles, a tactile surface sensor was developed to provide improved odometry determination for different ground conditions. The integration of the measurement data of the pressure sensor and the use of an improved model to determine the contact points and to improve the odometry calculation are the main objectives of this work. This is achieved by calculating the centre of gravity of the two tracks separately, using the measurement data of the pressure sensor and the local coordinates <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(x,y)$</tex> of each of the measurement points. The sensor concept was tested and evaluated on different grounds and terrains. The system can be used as a predictive model for tracked vehicle traversability and to ensure a stable position when straight manipulation tasks must be performed on rough terrain.

A free gait algorithm for quadrupedal walking machines