Chandana Paul

Design and control of tensegrity robots for locomotion

The static properties of tensegrity structures have been widely appreciated in civil engineering as the basis of extremely lightweight yet strong mechanical structures. However, the dynamic properties and their potential utility in the design of robots have been relatively unexplored. This paper introduces robots based on tensegrity structures, which demonstrate that the dynamics of such structures can be utilized for locomotion. Two tensegrity robots are presented: TR3, based on a triangular tensegrity prism with three struts, and TR4, based on a quadrilateral tensegrity prism with four struts. For each of these robots, simulation models are designed, and automatic design of controllers for forward locomotion are performed in simulation using evolutionary algorithms. The evolved controllers are shown to be able to produce static and dynamic gaits in both robots. A real-world tensegrity robot is then developed based on one of the simulation models as a proof of concept. The results demonstrate that tensegrity structures can provide the basis for lightweight, strong, and fault-tolerant robots with a potential for a variety of locomotor gaits

Low-bandwidth reflex-based control for lower power walking: 65 km on a single battery charge

No legged walking robot yet approaches the high reliability and the low power usage of a walking person, even on flat ground. Here we describe a simple robot which makes small progress towards that goal. Ranger is a knee-less four-legged ‘bipedal’ robot which is energetically and computationally autonomous, except for radio controlled steering. Ranger walked 65.2 km in 186,076 steps in about 31 h without being touched by a human with a total cost of transport [TCOT ≡ P/mgv ] of 0.28, similar to human’s TCOT of ≈ 0.3. The high reliability and low energy use were achieved by: (a) development of an accurate bench-test-based simulation; (b) development of an intuitively tuned nominal trajectory based on simple locomotion models; and (c) offline design of a simple reflex-based (that is, event-driven discrete feed-forward) stabilizing controller. Further, once we replaced the intuitively tuned nominal trajectory with a trajectory found from numerical optimization, but still using event-based control, we could further reduce the TCOT to 0.19. At TCOT = 0.19, the robot’s total power of 11.5 W is used by sensors, processors and communications (45%), motor dissipation (≈34%) and positive mechanical work (≈21%). Ranger’s reliability and low energy use suggests that simplified implementation of offline trajectory optimization, stabilized by a low-bandwidth reflex-based controller, might lead to the energy-effective reliable walking of more complex robots.

Morphological computation: A basis for the analysis of morphology and control requirements

Abstract The fact that the morphology of a robot affects its control requirements has become increasingly evident in robotics. Not only does the morphology determine the behaviors that can be performed, but also the amount of control required for these behaviors. Particularly in systems where behavior is obtained through purely sensory-motor interactions of the body with the environment, the morphology is of prime importance. Nonetheless, even in other robotic systems, a relationship has been found to exist between morphology and control requirements, in that some morphologies yield themselves to being more easily controlled than others. This relationship was first observed and characterized by Pfeifer as the morphology and control trade-off [R. Pfeifer, C. Scheier, Understanding Intelligence, MIT Press, Cambridge, MA, 1999], but the mechanisms underlying this relationship have been unclear. However, the discovery of morphological computation, 1 [C. Paul, Investigation of Morphology and Control in Biped Locomotion, Ph.D. Thesis, Department of Computer Science, University of Zurich, Switzerland, 2004], the phenomenon that computation can be obtained through interactions of physical form, elucidates a possible mechanism underlying this relationship. The fact that simple physical interactions give rise to computation indicates the theoretical possibility for the dynamics of the morphology to play a computational role in the system, and thereby to subsume part of the role of control. Thus, it may serve to analyse the relationship between morphology and control, and guide the design of robots with reduced control requirements. The goal of the paper is to explore this possibility. The paper introduces the concept of morphological computation in the context of robot morphology, discusses its potential role in the morphology and control trade-off, and then uses it as a basis to develop a heuristic for the design of robots with reduced control requirements. The heuristic is then tested through experiments to validate its accuracy. The preliminary results are promising, and suggest that morphological computation can be a suitable framework for the analysis of morphology and control requirements.

Development of a human neuro-musculo-skeletal model for investigation of spinal cord injury

This paper describes a neuro-musculo-skeletal model of the human lower body which has been developed with the aim of studying the effects of spinal cord injury on locomotor abilities. The model represents spinal neural control modules corresponding to central pattern generators, muscle spindle based reflex pathways, golgi tendon organ based pathways and cutaneous reflex pathways, which are coupled to the lower body musculo-skeletal dynamics. As compared to other neuro-musculo-skeletal models which aim to provide a description of the possible mechanisms involved in the production of locomotion, the goal of the model here is to understand the role of the known spinal pathways in locomotion. Thus, while other models focus primarily on functionality at the overall system level, the model here emphasizes functional and topological correspondance with the biological system at the level of the subcomponents representing spinal pathways. Such a model is more suitable for the detailed investigation of clinical questions related to spinal control of locomotion. The model is used here to perform preliminary experiments addressing the following issues: (1) the significance of spinal reflex modalities for walking and (2) the relative criticality of the various reflex modalities. The results of these experiments shed new light on the possible role of the reflex modalities in the regulation of stance and walking speed. The results also demonstrate the use of the model for the generation of hypothesis which could guide clinical experimentation. In the future, such a model may have applications in clinical diagnosis, as it can be used to identify the internal state of the system which provides the closest behavioral fit to a patient’s pathological condition.

Gait production in a tensegrity based robot

The design of legged robots for movement has usually been based on a series of rigid links connected by actuated or passively compliant joints. However, the potential utility of tensegrity, in which form can be achieved using a disconnected set of rigid elements connected by a continuous network of tensile elements, has not been considered in the design of legged robots. This paper introduces the idea of a legged robot based on a tensegrity structure, and demonstrates that the dynamics of such structures can be utilized for locomotion. A mobile robot based on a triangular tensegrity prism is presented, which is actuated by contraction of its transverse cables. The automatic design of a controller architecture for forward locomotion is performed in simulation using a genetic algorithm which demonstrates that the structure can generate multiple effective gait patterns for forward locomotion. A real world tensegrity robot is implemented based on the simulated robot, which is shown to be capable of producing forward locomotion. The results suggest that a tensegrity structure can provide the basis for extremely lightweight and robust mobile robots

Evolutionary form-finding of tensegrity structures

Tensegrity structures are stable 3-dimensional mechanical structures which maintain their form due to an intricate balance of forces between disjoint rigid elements and continuous tensile elements. Tensegrity structures can give rise to lightweight structures with high strength-to-weight ratios and their utility has been appreciated in architecture, engineering and recently robotics. However, the determination of connectivity patterns of the rigid and tensile elements which lead to stable tensegrity is challenging. Available methods are limited to the use of heuristic guidelines, hierarchical design based on known components, or mathematical methods which can explore only a subset of the space. This paper investigates the use of evolutionary algorithms in the form-finding of tensegrity structures. It is shown that an evolutionary algorithm can be used to explore the space of arbitrary tensegrity structures which are difficult to design using other methods, and determine new, non-regular forms. It suggests that evolutionary algorithms can be used as the basis for a general design methodology for tensegrity structures.

The road less travelled: morphology in the optimization of biped robot locomotion

Stable bipedal locomotion has been achieved using coupled evolution of morphology and control of a 5-link biped robot in a physics-based simulation environment. The robot was controlled by a closed loop recurrent neural network controller. The goal was to study the effect of macroscopic, midrange and microscopic changes in mass distribution along the biped skeleton to ascertain whether optimal morphology and control pairs could be discovered. The sensor-motor coupling determined that small changes in morphology manifest themselves as large changes in the performance of the biped, which were exploited by the optimization process. In this way, mechanical design and controller optimization were reduced to a single process, and more mutually optimized designs resulted. This work points to alternative routes for efficient automated and manual biped optimization.

Making Evolution an Offer It Can't Refuse: Morphology and the Extradimensional Bypass

In this paper, locomotion of a biped robot operating in a physics-based virtual environment is evolved using a genetic algorithm, in which some of the morphological and control parameters of the system are under evolutionary control. It is shown that stable walking is achieved through coupled optimization of both the controller and the mass ratios and mass distributions of the biped. It was found that although the size of the search space is larger in the case of coupled evolution of morphology and control, these evolutionary runs outperform other runs in which only the biped controller is evolved. We argue that this performance increase is attributable to extradimensional bypasses, which can be visualized as adaptive ridges in the fitness landscape that connect otherwise separated, sub-optimal adaptive peaks. In a similar study, a different set of morphological parameters are included in the evolutionary process. In this case, no significant improvement is gained by coupled evolution. These results demonstrate that the inclusion of the correct set of morphological parameters improves the evolution of adaptive behaviour in simulated agents.

Locomoting with Less Computation but More Morphology

Biped walking is one of the most graceful movements observed in humans. Today’s humanoid robots, despite their undeniably impressive performance, are still a long way from the elegance and grace found in Nature. To narrow the gap between natural and artificial systems, we propose to rely more on morphology, intrinsic dynamics, and less on raw computation. This paper documents a series of simulated and real “pseudo-passive” dynamic biped walkers in which computation is traded off for good morphology, that is, adequate mechanical design and appropriate material properties These two factors are parameterized, and the resulting solution space is explored in simulation. Interesting solutions are then realized in the real world. Our experiments show that successful pseudo-passive walkers with a good morphology locomote by converting oscillatory energy into forward movement.

Redundancy in the control of robots with highly coupled mechanical structures

This paper investigates the hypothesis that robots based on highly coupled mechanical structures can give rise to redundancy in control. Highly coupled mechanical structures have the property that actuation at one location can translate into movement at multiple locations, and conversely, movement at one location can be caused by multiple actuators. Due to this property, multiple control strategies may exist for a single behavior. Tensegrity structures which have recently been shown to form the basis for successful locomotor robots (Paul et al., 2005), have highly coupled mechanical structures. Thus, as a case study, it was of interest to investigate whether these new tensegrity based robots could offer a high degree of redundancy of control. This was investigated on two robots, based on three and four strut tensegrity prisms. Control strategies for locomotion were evolved using a genetic algorithm in simulation, and the evolved behaviors were compared. It was found that multiple control strategies existed for forward locomotion in both structures, and that qualitatively similar behavior could be obtained with significantly different control strategies. This indicated that a considerable degree of redundancy could exist in the control of robots based on highly coupled mechanical structures.