We report on our empirical studies of a new controller for a two-link brachiating robot. Motivated by the pendulum-like motion of an ape's brachiation, we encode this task as the output of a "target dynamical system". Numerical simulations indicate that the resulting controller solves a number of brachiation problems that we term the "ladder", "swing-up", and "rope" problems. Preliminary analysis provides some explanation for this success. The proposed controller is implemented on a physical system in our laboratory. The robot achieves behaviors including "swing locomotion" and "swing up" and is capable of continuous locomotion over several rungs of a ladder. We discuss a number of formal questions whose answers will be required to gain a full understanding of the strengths and weaknesses of this approach.

/pdf/a-brachiating-robot-controller-14bvok4wq1.pdf

A brachiating robot controller

Deals with a new type of dynamically moving mobile robot modeling a gibbon, namely a long armed ape, that moves branch to branch swinging its body like a pendulum. The manner of moving like a gibbon is called brachiation. The authors present the method to control the brachiation robot and show the results of simulation using a 2-link-model robot. The most difficult subject in this study is how to control it naturally, dynamically and with taking advantage of the gravity force. They introduce a heuristic approach to generate the driving forces by exercising motions to move by the robot itself, and show that the interpolation by CMAC (cerebellar model arithmetic computer) between the generated forces in some situations makes new forces suitable to inexperienced ones. They also show that the proposed control system using CMAC gives a natural and dynamical motion of the brachiation robot even under disturbances. >

A study on the brachiation type of mobile robot (heuristic creation of driving input and control using CMAC)

This review is designed to evaluate and interpret studies relevant to the locomotory mode known as brachiation, particularly as performed by the Hylobatid apes: the gibbon and siamang species. The older literature and its conclusions are evaluated against recent work performed by the author and other research groups working on brachiation models, either computer simulations or physical robots. The gibbon displays two types of brachiation: continuous contact, analogous to walking, and ricochetal, analogous to running. Both brachiation gaits display substantial pendular exchange between kinetic and potential energy. However, the fundamental feature of either of these gaits is the minimization of collisional energy loss. Collisional energy loss due to discontinuities in the trajectory of the center of mass is emerging as key in understanding locomotion using limbs in any terrestrial environment. The insight gained from this perspective applied to gibbon locomotion demonstrates that this is a critical factor in understanding many of the maneuvers employed by these animals, and can provide novel new interpretations of the morphological specializations that characterize the group. It is observed that these animals could brachiate using either totally active (muscle powered) or totally passive (nonmuscular) mechanisms. The active option would be metabolically costly, but provides substantial motion plasticity, while the passive option has the potential for profound economy, but does not allow a means to effectively contend with the inconsistencies present in the animal's natural environment. The conclusion is that the body form of brachiators and the locomotion behaviors they exhibit are a compromise between these two extremes, and these features of the gibbon's biology can only be understood by recognizing the role of collisional enerlgy loss and evaluating both passive and active motion options together. Yrbk Phys Anthropol 47:100–117, 2004. © 2004 Wiley-Liss, Inc.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ajpa.20156

New perspectives on brachiation mechanics

Complex behavior is difficult to obtain using an unsupervised leaning method because of the enormous search space required. In this paper, we propose the hierarchical behavior controller which consists of three types of modules: behavior coordinator, behavior controller and feedback controller. We also propose a new learning algorithm for the behavior coordinator and the behavior controller that consists of some sub-coordinators and some sub-controllers, respectively. This algorithm selects a deficient one by evaluating each sub-coordinator or sub-controller using multiple regression analysis based on previously obtained evaluation values. This can reduce the search area and the learning times by avoiding the necessity of trying to tune good sub-coordinators or sub-controllers. The hierarchical behavior controller is applied to the problem of controlling a seven-link brachiation robot, which moves dynamically from branch to branch like gibbon swinging its body.

Learning method for hierarchical behavior controller

In this paper, we present a control method to realize smooth continuous brachiation. The target brachiation is basically divided into two actions: a swing action and a locomotion action. In order to realize the continuous brachiation effectively and smoothly, it is necessary to start the swing action as soon as the robot grasps the front target bar at the end of the locomotion action. The collision, which occurs at the moment the robot grips the target bar, affects the pendulum motion of the robot. The action of bending the elbow joint of the swinging arm is proposed in order to solve this gripping problem. The elbow-bending action enables the robot to decrease the impact forces and use the excess mechanical energy after the end of the locomotion phase. Thus, there is no loss of energy and waste of time during the subsequent swing phase. Experimental results show that the robot can successfully achieve smooth, continuous brachiation.

A study on a brachiation controller for a multi-locomotion robot — realization of smooth, continuous brachiation

This paper deals with a new type of mobile robot, the brachiation robot, that makes use of the swing of a pendulum due to gravity, showing a simulation method with some results of its continuous mode during one period from the initial static condition to compute one cycle of the transfer motion. This type of robot can make use of energy stored by swing, thus can move with little energy induced. The problem in this study is to show the simulation method for the discontinuous motion, since the brachiation motion involves the switching of the swing supporting arms as a monkey does in the branch transfer motion. This paper shows a computational method of this discontinuous motion and also the energy evaluation in the brachiation motions, after introducing a new mobile mechanism. Then it becomes possible to evaluate such an oscillation effect during a period of brachiation motion, including the motion behavior and consumed energy depending on motion modes. Thus, this paper gives some insights for designing the structure and control method of a new brachiation type of robot. >

Brachiation type of mobile robot

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Brachiation type of mobile robot