Self-organized adaptive legged locomotion in a compliant quadruped robot

In this contribution we present experiments of an adaptive locomotion controller on a compliant quadruped robot. The adaptive controller consists of adaptive frequency oscillators in different configurations and produces dynamic gaits such as bounding and jumping. We show two main results: (1) The adaptive controller is able to track the resonant frequency of the robot which is a function of different body parameters (2) controllers based on dynamical systems as we present are able to “recognize” mechanically intrinsic modes of locomotion, adapt to them and enforce them. More specifically the main results are supported by several experiments, showing first that the adaptive controller is constantly tracking body properties and readjusting to them. Second, that important gait parameters are dependent on the geometry and movement of the robot and the controller can account for that. Third, that local control is sufficient and the adaptive controller can adapt to the different mechanical modes. And finally, that key properties of the gaits are not only depending on properties of the body but also the actual mode of movement that the body is operating in. We show that even if we specify the gait pattern on the level of the CPG the chosen gait pattern does not necessarily correspond to the CPG’s pattern. Furthermore, we present the analytical treatment of adaptive frequency oscillators in closed feedback loops, and compare the results to the data from the robot experiments.

Motion control of a snake robot moving between two non-parallel planes

A control method that makes the head of a snake robot follow an arbitrary trajectory on two non-parallel planes, including coexisting sloped and flat planes, is presented. We clarify an appropriate condition of contact between the robot and planes and design a controller for the part of the robot connecting the two planes that satisfies the contact condition. Assuming that the contact condition is satisfied, we derive a simplified model of the robot and design a controller for trajectory tracking of the robot’s head. The controller uses kinematic redundancy to avoid violating the limit of the joint angle and a collision between the robot and the edge of a plane. The effectiveness of the proposed method is demonstrated in experiments using an actual robot.     

Development of wheel-less snake robot with two distinct gaits and gait transition capability

Snake robots are mostly designed based on single mode locomotion. However, single mode gait most likely could not work effectively when the robot is subject to an unstructured working environment with different measures of terrain complexity. As a solution, mixed mode locomotion is proposed in this paper by synchronizing two types of gaits known as serpentine and wriggler gaits used for non-constricted and narrow space environments, respectively, but for straight line locomotion only. A gait transition algorithm is developed to efficiently change the gait from one to another. This study includes the investigation on kinematics analysis followed by dynamics analysis while considering related structural constraints for both gaits. The approach utilizes the speed of the serpentine gait for open area locomotion and exploits the narrow space access capability of the wriggler gait. Hence, it can increase motion flexibility in view of the fact that the robot is able to change its mode of locomotion according to the working environment.     

Hierarchical control structure of a multilegged robot for environmental adaptive locomotion

We propose a biomimetic, two-layered, hierarchical control structure for adaptive locomotion of a hexapod robot. In this structure, the lower layer consists of six uniform subsystems. Each subsystem interacts locally with its neighboring subsystems, and autonomously controls its own leg movements according to the weighted sum of three basic vector fields that represent the three basic motion patterns of the robot body. The upper-layer controller decides the intended body movement, and sends the lower-layer controllers three variables as the weights of each basic vector field. This approach greatly reduces the communication between the two layers, and contributes to real-time adaptive locomotion. 3D dynamic simulations, as well as experiments with a real modularized hexapod robot, show the effectiveness of this hierarchical structure. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001     

Correction to: Joint failure recovery for snake robot locomotion using a shape-based approach

Artificial Life and Robotics -     

Development of a new spinning gait for a planar snake robot using central pattern generators

In this paper, we first present dynamic equation of n-link snake robot using Lagrange’s method in a simplified matrix form and verify them experimentally. Next, we introduce a new locomotion mode called spinning gait. Central pattern generators (CPGs) are used for online gait generation. To realize spinning gait, genetic algorithm is used to find optimal CPG network parameters. We illustrate both theoretically, using derived robot dynamics and experimentally that the CPG-based online gait generation method allows continuous and rather smooth transitions between gaits. Lastly, we present an application where the snake robot is guided from an initial to final position while avoiding obstacles by changing CPG parameters.     

Development of adaptive locomotion of a caterpillar-like robot based on a sensory feedback CPG model

This paper presents a novel control mechanism for generating adaptive locomotion of a caterpillar-like robot in complex terrain. Inspired by biological findings in studies of the locomotion of the lamprey, we employ sensory feedback integration for online modulation of the control parameters of a new proposed central pattern generator (CPG). This closed-loop control scheme consists of the following stages: First, touch sensor information is processed and transformed into module states. Then, reactive strategies that determine the mapping between module states and sensory inputs are generated according to an analysis of the module states. Finally, by means of a genetic algorithm, adaptive locomotion is achieved by optimising the amount and speed of sensory input that is fed back to the CPG model. Incorporating the closed-loop controller in a caterpillar-like robot, both simulation and real on-site experiments are carried out. The results confirm the effectiveness of the control system, based on which the robot flexibly adapts to, and manages to crawl across the complex terrain.     

An adaptive locomotion controller for a hexapod robot: CPG,kinematics and force feedback

Insects can perform versatile locomotion behaviors such as multiple gaits, adapting to different terrains, fast escaping, etc. However, most of the existing bio-inspired legged robots do not possess such walking ability, especially when they walk on irregular terrains. To tackle this challenge, a central pattern generator （CPG）-based locomotion control methodology is proposed, integrated with a contact force feedback function. In this approach, multiple gaits are produced by the CFG module. After passing through a post-processing circuit and a delay-line, the control signal is fed into six trajectory generators to generate predefined feet trajectories for the six legs. Then, force feedback is employed to adjust these trajectories so as to adapt the robot to rough terrains. Finally the regulated trajectories are sent to inverse kinematics modules such that the position control instructions are generated to control the actuators. In both simulations and real robot experiments, we consistently show that the robot can perform sophisticated walking patterns. What is more, the robot can use the force feedback mechanism to deal with the irregularity in rough terrain. With this mechanism, the stability and adaptability of the robot are enhanced. In conclusion, the CPG-base control is an effective approach for legged robots and the force feedback approach is able to improve walking ability of the robots, especially when they walk on irregular terrains.     

Development of a separable search-and-rescue robot composed of a mobile robot and a snake robot

Abstract

In this study, we propose a new robot system consisting of a mobile robot and a snake robot. The system works not only as a mobile manipulator but also as a multi-agent system by using the snake robot's ability to separate from the mobile robot. Initially, the snake robot is mounted on the mobile robot in the carrying mode. When an operator uses the snake robot as a manipulator, the robot changes to the manipulator mode. The operator can detach the snake robot from the mobile robot and command the snake robot to conduct lateral rolling motions. In this paper, we present the details of our robot and its performance in the World Robot Summit.     

Study of lower level adaptive walking in the sagittal plane by a biped locomotion robot

Walking according to changes in the environment is called adaptive walking. We define lower level adaptive walking as a walk consisting only of trajectory control and walk-pattern generation. The purpose of this study was to realize lower level adapting walking in the sagittal plane by a biped locomotion robot in indoor space. In this paper, we propose a simplified procedure of walk-pattern generation, which is that walk patterns for various environments are generated by adjusting and combining the basic walk patterns which have previously been given for typical environments. Based on this idea, walking experiments were carried out for various environments. As a result, dynamic walking in a flat plane (about 1.5 s/step with a 0.3 m step width), changes of the step width in walking, and walking in various environments combined from a flat plane, an obstacle (such as a pipe) and a stair (up and down) were realized.     

Legged robot locomotion and gymnastics

The learning and control space of real-world autonomous agents are often many-dimensional, growing, and unbounded in nature. Such agents exhibit adaptive, incremental, exploratory, and sometimes explosive learning behaviors. Learning in adaptive neurofuzzy control, however, is often referred to as global training with a large set of random examples and a very low learning rate. This type of controller is not reorganizable; it cannot explain exploratory learning behaviors as exhibited by human and animal species. A theory of coordinated computational intelligence (CCI) is proposed in this paper which leads to a reorganizable multiagent cerebellar architecture for intelligent control. The architecture is based on the hypotheses that (1) a cerebellar system consists of a school of relatively simple and cognitively identifiable semiautonomous neurofuzzy agents; (2) autonomous control is the result of cerebellar agent fine-tuning and coordination rather than complicate computation; and (3) learning is accomplished via individual cerebellar agent learning and coordinated discovery in a learning-tuning-brainstorming process. Agent oriented decomposition and coordination algorithms are introduced; necessary and sufficient conditions are established for cerebellar agent discovery and common sense cerebellar motion law discovery. Nesting, safety, layering, and autonomy-four principles are analytically formulated for the reorganization of neurofuzzy agents.     

Analysis of creeping locomotion of a snake-like robot

Snakes perform many kinds of movement adapted to the environment. Utilizing the snake (its forms and motion) as a model to develop a snake-like robot, that performs the snake's function, is important for generating a new type of locomotion and expanding the possible uses of robots. In this study, we developed a simulator to simulate the creeping locomotion of the snake-like robot, in which the robot dynamics is modeled and the interaction with the environment is considered through Coulomb friction. This simulator makes it possible to analyze creeping locomotion with normaldirection slip, adding to the glide along the tangential direction. Through the developed simulator, we investigate the snake-like robot creeping locomotion which is generated only by swinging each of the joints from side to side and discuss the optimal creeping locomotion of the snake-like robot that is adapted to the environment.     

A robot leg with compliant tarsus and its neural control for efficient and adaptive locomotion on complex terrains

Insects, like dung beetles, show fascinating locomotor abilities. They can use their legs to walk on complex terrains (e.g., rocky and curved surfaces) and to manipulate objects. They also exploit their compliant tarsi, increasing the contact area between the legs and surface, to enhance locomotion, and object manipulation efficiency. Besides these biomechanical components, their neural control allows them to move at a proper frequency with respect to their biomechanical properties and to quickly adapt their movements to deal with environmental changes. Realizing these complex achievements on artificial systems remains a grand challenge. As a step towards this direction, we present here our first prototype of an artificial dung beetle-like leg with compliant tarsus by analyzing real dung beetle legs through \(\mu\)CT scans. Compliant tarsus was designed according to the so-called fin ray effect. Real robot experiments show that the leg with compliant tarsus can efficiently move on rocky and curved surfaces. We also apply neural control, based on a central pattern generator (CPG) circuit and synaptic plasticity, to autonomously generate a proper moving frequency of the leg. The controller can also adapt the leg movement to deal with environmental changes, like different treadmill speeds, within a few steps.     

Temporal gait control of a quadruped robot

The design and control of a four-legged robot for operation on vertical surfaces is described. The requirement that the robot trajectory be continually modifiable on-line in response to external sensor data is addressed with the development of a temporal gait control strategy. The ensuing gait automatically converges to various classical gaits for straight-line, turning and spinning maneuvres, and naturally accommodates transitions between these. Simulation results are presented to demonstrate the performance of this control strategy.     

Robust and adaptive door operation with a mobile robot

Intelligent Service Robotics - The ability to deal with articulated objects is very important for robots assisting humans. In this work, a framework to robustly and adaptively operate common doors,...     

Adaptive gait control for a walking robot

Walking vehicles have the potential to emulate the superior off-road mobility of biological systems. However, it is important to make the walking machine terrain adaptive and versatile, and to minimize man's role as an operator in order to realize this potential. Terrain adaptive locomotion involves intelligent foothold selection and the control of gait to produce the desired motion. This requires a departure from the idealized, structured stepping patterns for statically stable gaits which have been the object of considerable research. A modified wave gait is used to demonstrate that it is possible for the vehicle velocity to be varied continuously in accordance with higher level commands even with irregular, asymmetric, and changing support patterns, A varying duty factor is employed to enable optimal leg cycling frequencies. Implementation of gait control algorithms and results from a computer simulation are also presented.     

Circling turning locomotion of a new multiple closed-chain-legs robot with hybrid-driven mechanism

A multi-legged robot based on a hybrid-driven mechanism is presented in this paper as an improvement of the legged robot based on crank-driven linkage mechanism. A hybrid-driven mechanism containing a full-rotational degree of freedom (DOF) and a linear translational DOF was obtained after a series of foot trajectory analyses on the Jansen mechanism. The stance phase trajectory of this hybrid-driven mechanism can maintain horizontality regardless of the length adjustment of the linear DOF. A turning gait of a hexapod robot based on this hybrid-driven mechanism was proposed, such that all of the legs had an identical crank angular speed, and the robot turned its orientation through different linear servo controls on the legs of the two sides. Simulation and experimental results showed that the hexapod robot could realize the turning gait when the legs of the two sides applied different length adjustments. The body center trajectories in all cases were approximate to a circle, and the smallest turning radius was close to the length of the robot. Moreover, the magnitude of the pitch and roll angles, and body center fluctuation in the simulations was all small, indicating that the hexapod robot based on the hybrid-driven mechanism was stable during the turning locomotion.     

Vision-based interception of a moving target with a nonholonomic mobile robot

A novel vision-based scheme is presented for driving a nonholonomic mobile robot to intercept a moving target. The proposed method has a two-level structure. On the lower level, the pan–tilt platform carrying the on-board camera is controlled so as to keep the target as close as possible to the center of the image plane. On the higher level, the relative position of the target is retrieved from its image coordinates and the camera pan–tilt angles through simple geometry, and used to compute a control law which drives the robot to the target. Various possible choices are discussed for the high-level robot controller, and the associated stability properties are rigorously analysed. The proposed visual interception method is validated through simulations as well as experiments on the mobile robot MagellanPro.