Technical Report: A Contact-aware Feedback CPG System for Learning-based Locomotion Control in a Soft Snake Robot

Integrating contact-awareness into a soft snake robot and efficiently controlling its locomotion in response to contact information present significant challenges. This paper aims to solve contact-aware locomotion problem of a soft snake robot through developing bio-inspired contact-aware locomotion controllers. To provide effective contact information for the controllers, we develop a scale covered sensor structure mimicking natural snakes' \textit{scale sensilla}. In the design of control framework, our core contribution is the development of a novel sensory feedback mechanism of the Matsuoka central pattern generator (CPG) network. This mechanism allows the Matsuoka CPG system to work like a "spine cord" in the whole contact-aware control scheme, which simultaneously takes the stimuli including tonic input signals from the "brain" (a goal-tracking locomotion controller) and sensory feedback signals from the "reflex arc" (the contact reactive controller), and generate rhythmic signals to effectively actuate the soft snake robot to slither through densely allocated obstacles. In the design of the "reflex arc", we develop two types of reactive controllers -- 1) a reinforcement learning (RL) sensor regulator that learns to manipulate the sensory feedback inputs of the CPG system, and 2) a local reflexive sensor-CPG network that directly connects sensor readings and the CPG's feedback inputs in a special topology. These two reactive controllers respectively facilitate two different contact-aware locomotion control schemes. The two control schemes are tested and evaluated in the soft snake robot, showing promising performance in the contact-aware locomotion tasks. The experimental results also further verify the benefit of Matsuoka CPG system in bio-inspired robot controller design.Comment: 17 pages, 19 figure

Control of snake robots with switching constraints: trajectory tracking with moving obstacle

We propose control of a snake robot that can switch lifting parts dynamically according to kinematics. Snakes lift parts of their body and dynamically switch lifting parts during locomotion: e.g. sinus-lifting and sidewinding motions. These characteristic types of snake locomotion are used for rapid and efficient movement across a sandy surface. However, optimal motion of a robot would not necessarily be the same as that of a real snake as the features of a robot’s body are different from those of a real snake. We derived a mathematical model and designed a controller for the three-dimensional motion of a snake robot on a two-dimensional plane. Our aim was to accomplish effective locomotion by selecting parts of the body to be lifted and parts to remain in contact with the ground. We derived the kinematic model with switching constraints by introducing a discrete mode number. Next, we proposed a control strategy for trajectory tracking with switching constraints to decrease cost function, and to satisfy the conditions of static stability. In this paper, we introduced a cost function related to avoidance of the singularity and the moving obstacle. Simulations and experiments demonstrated the effectiveness of the proposed controller and switching constraints

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

An Overview of Legged Robots

The objective of this paper is to present the evolution and the state-of-theart in the area of legged locomotion systems. In a first phase different possibilities for mobile robots are discussed, namely the case of artificial legged locomotion systems, while emphasizing their advantages and limitations. In a second phase an historical overview of the evolution of these systems is presented, bearing in mind several particular cases often considered as milestones on the technological and scientific progress. After this historical timeline, some of the present day systems are examined and their performance is analyzed. In a third phase are pointed out the major areas for research and development that are presently being followed in the construction of legged robots. Finally, some of the problems still unsolved, that remain defying robotics research, are also addressed.N/

Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm

Manoeuvrable robot commonly has become the focus of the latest heated issues especially in applications that involved disaster rescue, military missions and underwater or extra-terrestrial explorations. Currently, the manoeuvrable robot is controlled manually by the operator and it’s a wheeled type. It is used for rescue missions to transport people from disaster area to the safe zone. However, the robot is incapable of moving automatically, and it goes through terrain or landscape like swarm. Therefore, a suitable platform is required to transport or for other uses especially in dangerous mission. It is very difficult to estimate the movement of the robot to avoid obstacles and choose the alternative path. Hence, this research presents the point-to-point gait identification or path planning of the behavious of the robot to manuever autonomously on both on-land and underwater environment. For the optimization, the robot will travel from one specific point to another with the predefined position within optimized gait and fastest time by using Ant Colony Optimization (ACO) technique. The algorithm being compared, between Ant Colony Algorithm (ACO) and the Particle Swarm Optimisation (PSO) in terms of time and distance. The ACO been chosen because of the positive feedback for rapid discovery and able to use in dynamic applications for example adapts to changes like new distances. The performance of the algorithm showed that the execution time of ACO is more realistic. Hence, Matlab is used to determine the best cost extracted from the ACO with the pre-define of number of iteration and the number of ants. The laboratory-scaled prototype for amphibious vehicle was developed to test the design controlled with ACO technique where Global Positioning System (GPS) is used for the coordination of the robot and Magnetometer for the position of the robot. The robot prototype is able to move autonomously and optimized by the ant colony optimization with predefined position and terrain condition © BEIESP

Mobile Robotics

The book is a collection of ten scholarly articles and reports of experiences and perceptions concerning pedagogical practices with mobile robotics.“This work is funded by CIEd – Research Centre on Education, project UID/CED/01661/2019, Institute of Education, University of Minho, through national funds of FCT/MCTES-PT.

Shape Control of a Snake Robot With Joint Limit and Self-Collision Avoidance

This paper proposes a shape control method for a snake robot, which maintains head position and orientation, and avoids joint limits and self-collision. We used a passive wheeled snake robot that can switch the grounded/lifted status of its wheels. We derived a kinematic model of the robot that represents its redundancy as both joint angles [the shape controllable points (SCPs)] and the null space of the control input. In the control method, the shape is changed by sequential control of the SCPs, and the null space of the control input is used for joint limit and self-collision avoidance. Jumps in control input do not occur, although the controlled variable and the model are switched. Simulations and an experiment were used to demonstrate the effectiveness of the proposed method

Mixed Integer Programming-Based Semiautonomous Step Climbing of a Snake Robot Considering Sensing Strategy

We propose a control method for semiautonomous step climbing by a snake robot. Our method is based on mixed integer quadratic programming to generate the reference trajectory of the head of the snake robot online. One of the features of the method is that it determines suitable positions and time duration in which to sense the surroundings before approaching the step. Furthermore, constraints on velocity and acceleration are taken into account, so that the snake robot can securely follow the generated trajectory. Our method was applied to a snake robot equipped with a laser range finder, which is used for step detection. Experiments were performed to verify the efficacy of the method