The purpose of this research is to imitate the motion of the crab, and to propose a new control strategy for hexapod robots. Referring to the proportion of a real crab, we construct a 12- actuator hexapod robot. Walking experiments are achieved by using a tripod gait, a metachronal gait and a paired metachronal gait. We observe the loading of actuators and compare the functionality of the gaits. A special feed-forward gait and the Zero Torque control strategy are added in the climbing experiment. A compressed rubber-wire carpet and wire dactyl claws are used to simulate the non-slip climbing condition. Our experiment results show that the loading condition of the pendulous tripod gait is better than conventional tripod gait, and the paired metachronal gait is better than metachronal gait. During climbing experiments, our robot walks on a vertical, an upside-down, and two transitional terrains.

This thesis aims to transfer knowledge from insect biology into a hexapod walking robot. The similarity of the robot model to the biological target allows the testing of hypotheses regarding control and behavioural strategies in the insect. Therefore, this thesis supports biorobotic research by demonstrating that robotic implementations are improved by using biological strategies and these models can be used to understand biological systems. Specifically, this thesis addresses two central problems in hexapod walking control: the single leg control mechanism and its control variables; and the different roles of the front, middle and hind legs that allow a decentralised architecture to co-ordinate complex behavioural tasks. To investigate these problems, behavioural studies on insect curve walking were combined with quantitative simulations. Behavioural experiments were designed to explore the control of turns of freely walking stick insects, Carausius morosus, toward a visual target. A program for insect tracking and kinematic analysis of observed motion was developed. The results demonstrate that the front legs are responsible for most of the body trajectory. Nonetheless, to replicate insect walking behaviour it is necessary for all legs to contribute with specific roles. Additionally, statistics on leg stepping show that middle and hind legs continuously influence each other. This cannot be explained by previous models that heavily depend on positive feedback controllers. After careful analysis, it was found that the hind legs could actively rotate the body while the middle legs move to the inside of the curve, tangentially to the body axis. The single leg controller is known to be independent from other legs but still capable of mechanical synchronisation. To explain this behaviour positive feedback controllers have been proposed. This mechanism works for the closed kinematic chain problem, but has complications when implemented in a dynamic model. Furthermore, neurophysiological data indicate that legs always respond to disturbances as a negative feedback controller. Additional experimental data presented herein indicates that legs continuously oppose forces created by other legs. This thesis proposes a model that has a velocity positive feedback control modulated via a subordination variable in cascade with a position negative feedback mechanism as the core controller. This allows legs to oppose external and internal forces without compromising inter-leg collaboration for walking. The single leg controller is implemented using a distributed artificial neural network. This network was trained with a wider range of movement to that so far found in the simulation model. The controller implemented with a plausible biological.

Many environments are inaccessible or hazardous for humans. Remaining debris after earthquake and fire, ship hulls, bridge installations, and oil rigs are some examples. For these environments, major effort is being placed into replacing humans with robots for manipulation purposes such as search and rescue, inspection, repair, and maintenance. Mobility, manipulability, and stability are the basic needs for a robot to traverse, maneuver, and manipulate in such irregular and highly obstructed terrain. Hexapod walking robots are as a salient solution because of their extra degrees of mobility, compared to mobile wheeled robots. However, it is essential for any multi-legged walking robot to maintain its stability over the terrain or under external stimuli. For manipulation purposes, the robot must also have a sufficient workspace to satisfy the required manipulability. Therefore, analysis of both workspace and stability becomes very important. An accurate and concise inverse kinematic solution for multi-legged robots is developed and validated. The closed-form solution of lateral and spatial reachable workspace of axially symmetric hexapod walking robots are derived and validated through simulation which aid in the design and optimization of the robot parameters and workspace. To control the stability of the robot, a novel stability margin based on the normal contact forces of the robot is developed and then modified to account for the geometrical and physical attributes of the robot. The margin and its modified version are validated by comparison with a widely known stability criterion through simulated and physical experiments. A control scheme is developed to integrate the workspace and stability of multi-legged walking robots resulting in a bio-inspired reactive control strategy which is validated experimentally.

Hexplorer is a six-legged walking robot developed at the University of Waterloo. The robot is controlled by a network of seven digital signal processors, six of which control three motors each, for a total of 18 motors. Brand new custom electronics were designed to house the digital signal processors and associated circuitry. A variable duty factor wave gait, developed by Yoneda et al. was simulated and implemented on the robot. Simulation required an in-depth kinematic analysis that was complicated by the mechanical design of parallel mechanism comprising the legs. These complications were handled in both simulation and implementation. However, due to mechanical issues Hexplorer walked for only one or two steps at a time.

Hexplorer is a six-legged walking robot developed at the University of Waterloo. The robot is controlled by a network of seven digital signal processors, six of which control three motors each, for a total of 18 motors. Brand new custom electronics were designed to house the digital signal processors and associated circuitry. A variable duty factor wave gait, developed by Yoneda et al. was simulated and implemented on the robot. Simulation required an in-depth kinematic analysis that was complicated by the mechanical design of parallel mechanism comprising the legs. These complications were handled in both simulation and implementation. However, due to mechanical issues Hexplorer walked for only one or two steps at a time.

This thesis sets up terrain parameters and locomotion strategies of a hexapod robot walking on variable and discontinuous terrain. Walking on this kind of terrain is the greatest advantage of legged robots compared with wheeled robots. First, establish a randomly distributed parameterized terrain. Second, set up morphological parameters and dimension parameters of the robot. Third, build kinematic model and generate continuous gaits of the robot, including crab gaits and turning gaits. The locomotion strategy can determine every AEP ,PEP and stride depending on terrain. Finally, verify the strategy through computer programming and find shorter path by calculating if foothold is available in advance. Because of applying randomly distributed parameterized terrain, in addition to describing the terrain more comprehensively, the terrain parameters can be adjusted easily according to different needs. This research will bring about more applications and developments of legged robots.

Walking machines may not be more common or faster than the transportations with wheels. It can¡¦t be ignored in the occasions of unknown terrain. This paper is going to discuss about how a walking machine get faster and be static stable. When the quadrupeds walk toward, the wide won¡¦t be changed. So that, longitudinal stability margin can take the place of stability margin to simplify gait problems. Meanwhile we can get the optimal gait. In the past researches, there is only one kind of walking type will be discussed in one time. This is because there are not so many relationships between different kinds of movement. If we take one step ahead to discuss the optimal gait, it will be more difficult. If there was a way to get into optimal gait from random initial position, we can connect one movement with the other. The velocity was constrained while the quadruped modal has had been made since 1968 by McGhee. We will try to change the working area to approve the performance. As to the researches of multi-legs walking machine, most of them talk about quadrupeds and hexapods. it will be less if the more legs we are talked about. To maintain stable tread, a walking machine request four legs at least. We can regard a quadruped as a unit, and divide a multi-leg working machine in to many quadrupeds. By using the method of quadruped analysis, we can simplify multi-legs gait algorithm problems.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / This paper presents an alternative solution to improve the locomotion system of a hexapod robot by artificial intelligence. Through an optimal design to achieve static stability, dynamic stability and optimize energy consumption through an autonomous system that is able to perform trajectories without any inconvenience. For the robot to move without flaws has certain restrictions in design (weight, size, materials, etc.) The hexapod has a high degree of movement and this allows many trajectories handle at the time of travel. Using sensors under certain working conditions we will obtain the necessary data and signals to satisfactorily comply with the hexapod robot design. / Revisión por pares

No description available.

The Defence, Peace, Safety and Security (DPSS) competency area within the Council for Scientific and Industrial Research (CSIR) has identified the need for the development of a robot that can operate in almost any land-based environment. Legged robots, especially hexapod (six-legged) robots present a wide variety of advantages that can be utilised in this environment and is identified as a feasible solution. The biggest advantage and main reason for the development of legged robots over mobile (wheeled) robots, is their ability to navigate in uneven, unstructured terrain. However, due to the complicated control algorithms needed by a legged robot, most literature only focus on navigation in even or relatively even terrains. This is seen as the main limitation with regards to the development of legged robot applications. For navigation in unstructured terrain, postural controllers of legged robots need fast and precise knowledge about the state of the robot they are regulating. The speed and accuracy of the state estimation of a legged robot is therefore very important. Even though state estimation for mobile robots has been studied thoroughly, limited research is available on state estimation with regards to legged robots. Compared to mobile robots, locomotion of legged robots make use of intermitted ground contacts. Therefore, stability is a main concern when navigating in unstructured terrain. In order to control the stability of a legged robot, six degrees of freedom information is needed about the base of the robot platform. This information needs to be estimated using measurements from the robot’s sensory system. A sensory system of a robot usually consist of multiple sensory devices on board of the robot. However, legged robots have limited payload capacities and therefore the amount of sensory devices on a legged robot platform should be kept to a minimum. Furthermore, exteroceptive sensory devices commonly used in state estimation, such as a GPS or cameras, are not suitable when navigating in unstructured and unknown terrain. The control and localisation of a legged robot should therefore only depend on proprioceptive sensors. The need for the development of a reliable state estimation framework (that only relies on proprioceptive information) for a low-cost, commonly available hexapod robot is identified. This will accelerate the process for control algorithm development. In this study this need is addressed. Common proprioceptive sensors are integrated on a commercial low-cost hexapod robot to develop the robot platform used in this study. A state estimation framework for legged robots is used to develop a state estimation methodology for the hexapod platform. A kinematic model is also derived and verified for the platform, and measurement models are derived to address possible errors and noise in sensor measurements. The state estimation methodology makes use of an Extended Kalman filter to fuse the robots kinematics with measurements from an IMU. The needed state estimation equations are also derived and implemented in Matlab®. The state estimation methodology developed is then tested with multiple experiments using the robot platform. In these experiments the robot platform captures the sensory data with a data acquisition method developed while it is being tracked with a Vicon motion capturing system. The sensor data is then used as an input to the state estimation equations in Matlab® and the results are compared to the ground-truth measurement outputs of the Vicon system. The results of these experiments show very accurate estimation of the robot and therefore validate the state estimation methodology and this study. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015