CPG-Based Gait Generation of the Curved-Leg Hexapod Robot with Smooth Gait Transition

Leg-body coordination strategies for obstacle avoidance and narrow space navigation of multi-segmented, legged robots

Introduction

Millipedes can avoid obstacle while navigating complex environments with their multi-segmented body. Biological evidence indicates that when the millipede navigates around an obstacle, it first bends the anterior segments of its corresponding anterior segment of its body, and then gradually propagates this body bending mechanism from anterior to posterior segments. Simultaneously, the stride length between pairs of legs inside the bending curve decreases to coordinate the leg motions with the bending mechanism of the body segments. In robotics, coordination between multiple legs and body segments during turning for navigating in complex environments, e.g., narrow spaces, has not been fully realized in multi-segmented, multi-legged robots with more than six legs.

Method

To generate the efficient obstacle avoidance turning behavior in a multi-segmented, multi-legged (millipede-like) robot, this study explored three possible strategies of leg and body coordination during turning: including the local leg and body coordination at the segment level in a manner similar to millipedes, global leg amplitude change in response to different turning directions (like insects), and the phase reversal of legs inside of turning curve during obstacle avoidance (typical engineering approach).

Results

Using sensory inputs obtained from the antennae located at the robot head and recurrent neural control, different turning strategies were generated, with gradual body bending propagation from the anterior to posterior body segments.

Discussion

We discovered differences in the performance of each turning strategy, which could guide the future control development of multi-segmented, legged robots.

Multi-constraint spatial coupling for the body joint quadruped robot and the CPG control method on rough terrain

Quadruped robots have frequently appeared in various situations, including wilderness rescue, planetary exploration, and nuclear power facility maintenance. The quadruped robot with an active body joint has better environmental adaptability than one without body joints. However, it is difficult to guarantee the stability of the body joint quadruped robot when walking on rough terrain. Given the above issues, this paper proposed a gait control method for the body joint quadruped robot based on multi-constraint spatial coupling (MCSC) algorithm. The body workspace of the robot is divided into three subspaces, which are solved for different gaits, and then coupled to obtain the stable workspace of the body. A multi-layer central pattern generator model based on the Hopf oscillator is built to realize the generation and switching of walk and trot gaits. Then, combined with the MCSC area of the body, the reflex adjustment strategy on different terrains is established to adjust the body's posture in real time and realize the robot's stable locomotion. Finally, the robot prototype is developed to verify the effectiveness of the control method. The simulation and experiment results show that the proposed method can reduce the offset of the swing legs and the fluctuation of the body attitude angle. Furthermore, the quadruped robot is ensured to maintain stability by dynamically modifying its body posture. The relevant result can offer a helpful reference for the control of quadruped robots in complex environments.

A CPG-Based Versatile Control Framework for Metameric Earthworm-Like Robotic Locomotion

Annelids such as earthworms are considered to have central pattern generators (CPGs) that generate rhythms in neural circuits to coordinate the deformation of body segments for effective locomotion. At present, the states of earthworm-like robot segments are often assigned holistically and artificially by mimicking the earthworms' retrograde peristalsis wave, which is unable to adapt their gaits for variable environments and tasks. This motivates the authors to extend the bioinspired research from morphology to neurobiology by mimicking the CPG to build a versatile framework for spontaneous motion control. Here, the spatiotemporal dynamics is exploited from the coupled Hopf oscillators to not only unify the two existing gait generators for restoring temporal-symmetric phase-coordinated gaits and discrete gaits but also generate novel temporal-asymmetric phase-coordinated gaits. Theoretical and experimental tests consistently confirm that the introduction of temporal asymmetry improves the robot's locomotion performance. The CPG-based controller also enables seamless online switching of locomotion gaits to avoid abrupt changes, sharp stops, and starts, thus improving the robot's adaptability in variable working scenarios.

TALBOT: A Track-Leg Transformable Robot

This article introduces a tracked-leg transformable robot, TALBOT. The mechanical and electrical design, control method, and environment perception based on LiDAR are discussed. The original tracked-leg transformable structure allows the robot to switch between the tracked and legged mode to achieve all-terrain adaptation. In the tracked mode, TALBOT is controlled by the method of differential speed between the two tracked feet. In the legged mode, TALBOT is controlled based on a bionic control strategy of the central pattern generator to realize the generation and conversion of gait. In addition, the robot is equipped with a LiDAR, through sensor preprocessing and optimization of the slam mapping algorithm, so that the robot achieves a better mapping effect. We tested the robot’s motion performance and the slam mapping effect, including going straight and turning in tracked and legged modes and building a map in an indoor environment.

Insect-Inspired Robots: Bridging Biological and Artificial Systems

This review article aims to address common research questions in hexapod robotics. How can we build intelligent autonomous hexapod robots that can exploit their biomechanics, morphology, and computational systems, to achieve autonomy, adaptability, and energy efficiency comparable to small living creatures, such as insects? Are insects good models for building such intelligent hexapod robots because they are the only animals with six legs? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying relevant and future directions in the field of hexapod robotics over the next decade. After an introduction in section (1), the sections will respectively cover the following three key areas: (2) biomechanics focused on the design of smart legs; (3) locomotion control; and (4) high-level cognition control. These interconnected and interdependent areas are all crucial to improving the level of performance of hexapod robotics in terms of energy efficiency, terrain adaptability, autonomy, and operational range. We will also discuss how the next generation of bioroboticists will be able to transfer knowledge from biology to robotics and vice versa.

Adaptive Walking Control for a Quadruped Robot on Irregular Terrain Using the Complex-Valued CPG Network

In this paper, we propose a CPG (central pattern generator) network control system using motor dynamics for the gait planning of a quadruped robot with a trot walking pattern to climb up and down a slope and turn back and follow the symmetry of route. The CPG unit model, which includes two DC motors model, has the ability to generate the periodic joint angle with complex-value parameters. Through plural feedback parameters, the CPG network can adjust the frequency and amplitude of an internal neuron model such as a robot meeting an irregular surface of a road. Using the stride length and frequency of robot joint angles, the distance of walking with a trot pattern can be calculated. In order to confirm the validity of the proposed control system, a quadruped robot is produced to implement the adaptive walking system.

Gait Optimization Method for Humanoid Robots Based on Parallel Comprehensive Learning Particle Swarm Optimizer Algorithm

To improve the fast and stable walking ability of a humanoid robot, this paper proposes a gait optimization method based on a parallel comprehensive learning particle swarm optimizer (PCLPSO). Firstly, the key parameters affecting the walking gait of the humanoid robot are selected based on the natural zero-moment point trajectory planning method. Secondly, by changing the slave group structure of the PCLPSO algorithm, the gait training task is decomposed, and a parallel distributed multi-robot gait training environment based on RoboCup3D is built to automatically optimize the speed and stability of bipedal robot walking. Finally, a layered learning approach is used to optimize the turning ability of the humanoid robot. The experimental results show that the PCLPSO algorithm achieves a quickly optimal solution, and the humanoid robot optimized possesses a fast and steady gait and flexible steering ability.

Attitude Trajectory Optimization to Ensure Balance Hexapod Locomotion

This paper proposes a simple attitude trajectory optimization method to enhance the walking balance of a large-size hexapod robot. To achieve balance motion control of a large-size hexapod robot on different outdoor terrains, we planned the balance attitude trajectories of the robot during walking and introduced how leg trajectories are generated based on the planned attitude trajectories. While planning the attitude trajectories, high order polynomial interpolation was employed with attitude fluctuation counteraction considered. Constraints that the planned attitude trajectories must satisfy during walking were well-considered. The trajectory of the swing leg was well designed with the terrain attitude considered to improve the environmental adaptability of the robot during the attitude adjustment process, and the trajectory of the support leg was automatically generated to satisfy the demand of the balance attitude trajectories planned. Comparative experiments of the real large-size hexapod robot walking on different terrains were carried out to validate the effectiveness and applicability of the attitude trajectory optimization method proposed, which demonstrated that, compared with the currently developed balance motion controllers, the attitude trajectory optimization method proposed can simplify the control system design and improve the walking balance of a hexapod robot.

Stability-Guaranteed and High Terrain Adaptability Static Gait for Quadruped Robots

Stability is a prerequisite for legged robots to execute tasks and traverse rough terrains. To guarantee the stability of quadruped locomotion and improve the terrain adaptability of quadruped robots, a stability-guaranteed and high terrain adaptability static gait for quadruped robots is addressed. Firstly, three chosen stability-guaranteed static gaits: intermittent gait 1&2 and coordinated gait are investigated. In addition, then the static gait: intermittent gait 1, which is with the biggest stability margin, is chosen to do a further research about quadruped robots walking on rough terrains. Secondly, a position/force based impedance control is employed to achieve a compliant behavior of quadruped robots on rough terrains. Thirdly, an exploratory gait planning method on uneven terrains with touch sensing and an attitude-position adjustment strategy with terrain estimation are proposed to improve the terrain adaptability of quadruped robots. Finally, the proposed methods are validated by simulations.

Static Balancing of Wheeled-legged Hexapod Robots

Locomotion over different terrain types, whether flat or uneven, is very important for a wide range of service operations in robotics. Potential applications range from surveillance, rescue, or hospital assistance. Wheeled-legged hexapod robots have been designed to solve these locomotion tasks. Given the wide range of feasible operations, one of the key operation planning issues is related to the robot balancing during motion tasks. Usually this problem is related with the pose of the robot’s center of mass, which can be addressed using different mathematical techniques. This paper proposes a new practical technique for balancing wheeled-legged hexapod robots, where a Biodex Balance System model SD (for static & dynamic) is used to obtain the effective position of the center of mass, thus it can be recalculated to its optimal position. Experimental tests are carried out to evaluate the effectiveness of this technique and modify and improve the position of hexapod robots’ center of mass.