Vytas SunSpiral

Design and Control of Compliant Tensegrity Robots Through Simulation and Hardware Validation

To better understand the role of tensegrity structures in biological systems and their application to robotics, the Dynamic Tensegrity Robotics Lab at NASA Ames Research Center, Moffett Field, CA, USA, has developed and validated two software environments for the analysis, simulation and design of tensegrity robots. These tools, along with new control methodologies and the modular hardware components developed to validate them, are presented as a system for the design of actuated tensegrity structures. As evidenced from their appearance in many biological systems, tensegrity (‘tensile–integrity’) structures have unique physical properties that make them ideal for interaction with uncertain environments. Yet, these characteristics make design and control of bioinspired tensegrity robots extremely challenging. This work presents the progress our tools have made in tackling the design and control challenges of spherical tensegrity structures. We focus on this shape since it lends itself to rolling locomotion. The results of our analyses include multiple novel control approaches for mobility and terrain interaction of spherical tensegrity structures that have been tested in simulation. A hardware prototype of a spherical six-bar tensegrity, the Reservoir Compliant Tensegrity Robot, is used to empirically validate the accuracy of simulation.

Design and evolution of a modular tensegrity robot platform

NASA Ames Research Center is developing a compliant modular tensegrity robotic platform for planetary exploration. In this paper we present the design and evolution of the platforms main hardware component, an untethered, robust tensegrity strut, with rich sensor feedback and cable actuation. Each strut is a complete robot, and multiple struts can be combined together to form a wide range of complex tensegrity robots. Our current goal for the tensegrity robotic platform is the development of SUPERball, a 6-strut icosahedron underactuated tensegrity robot aimed at dynamic locomotion for planetary exploration rovers and landers, but the aim is for the modular strut to enable a wide range of tensegrity morphologies. SUPERball is a second generation prototype, evolving from the tensegrity robot ReCTeR, which is also a modular, lightweight, highly compliant 6-strut tensegrity robot that was used to validate our physics based NASA Tensegrity Robot Toolkit (NTRT) simulator. Many hardware design parameters of the SUPERball were driven by locomotion results obtained in our validated simulator. These evolutionary explorations helped constrain motor torque and speed parameters, along with strut and string stress. As construction of the hardware has finalized, we have also used the same evolutionary framework to evolve controllers that respect the built hardware parameters.

Rapid prototyping design and control of tensegrity soft robot for locomotion

Co-robots that can effectively move with and operate alongside humans in a variety of conditions could revolutionize the utility of robots for a wide range of applications. Unfortunately, most current robotic systems have difficulty operating in human environments that people easily traverse, much less interact with people. Wheeled robots have difficulty climbing stairs or going over rough terrain. Heavy and powerful legged robots pose safety risks when interacting with humans. Compliant, lightweight tensegrity robots built from interconnected tensile (cables) and compressive (rods) elements are promising structures for co-robotic applications. This paper describes design and control of a rapidly prototyped tensegrity robot for locomotion. The software and hardware of this robot can be extended to build a wide range of tensegrity robotic configurations and control strategies. This rapid prototyping approach will greatly lower the barrier-of-entry in time and cost for research groups studying tensegrity robots suitable for co-robot applications.

DuCTT: A tensegrity robot for exploring duct systems

A robot with the ability to traverse complex duct systems requires a large range of controllable motions as well as the ability to grip the duct walls in vertical shafts. We present a tensegrity robot with two linked tetrahedral frames, each containing a linear actuator, connected by a system of eight actuated cables. The robot climbs by alternately wedging each tetrahedron within the duct and moving one tetrahedron relative to the other. We first introduce our physical prototype, called DuCTT (Duct Climbing Tetrahedral Tensegrity). We next discuss the inverse kinematic control strategy used to actuate the robot and analyze the controllers capabilities within a physics simulation. Finally, we discuss the hardware prototype and compare its performance with simulation.

Controlling tensegrity robots through evolution

Tensegrity structures (built from interconnected rods and cables) have the potential to offer a revolutionary new robotic design that is light-weight, energy-efficient, robust to failures, capable of unique modes of locomotion, impact tolerant, and compliant (reducing damage between the robot and its environment). Unfortunately robots built from tensegrity structures are difficult to control with traditional methods due to their oscillatory nature, nonlinear coupling between components and overall complexity. Fortunately this formidable control challenge can be overcome through the use of evolutionary algorithms. In this paper we show that evolutionary algorithms can be used to efficiently control a ball shaped tensegrity robot. Experimental results performed with a variety of evolutionary algorithms in a detailed soft-body physics simulator show that a centralized evolutionary algorithm performs 400% better than a hand-coded solution, while the multiagent evolution performs 800% better. In addition, evolution is able to discover diverse control solutions (both crawling and rolling) that are robust against structural failures and can be adapted to a wide range of energy and actuation constraints. These successful controls will form the basis for building high-performance tensegrity robots in the near future.

System design and locomotion of SUPERball, an untethered tensegrity robot

The Spherical Underactuated Planetary Exploration Robot ball (SUPERball) is an ongoing project within NASA Ames Research Centers Intelligent Robotics Group and the Dynamic Tensegrity Robotics Lab (DTRL). The current SUPERball is the first full prototype of this tensegrity robot platform, eventually destined for space exploration missions. This work, building on prior published discussions of individual components, presents the fully-constructed robot. Various design improvements are discussed, as well as testing results of the sensors and actuators that illustrate system performance. Basic low-level motor position controls are implemented and validated against sensor data, which show SUPERball to be uniquely suited for highly dynamic state trajectory tracking. Finally, SUPERball is shown in a simple example of locomotion. This implementation of a basic motion primitive shows SUPERball in untethered control.

Flop and Roll: Learning Robust Goal-Directed Locomotion for a Tensegrity Robot

Tensegrity robots are composed of compression elements (rods) that are connected via a network of tension elements (cables). Tensegrity robots provide many advantages over standard robots, such as compliance, robustness, and flexibility. Moreover, sphere-shaped tensegrity robots can provide non-traditional modes of locomotion, such as rolling. While they have advantageous physical properties, tensegrity robots are hard to control because of their nonlinear dynamics and oscillatory nature. In this paper, we present a robust, distributed, and directional rolling algorithm, “flop and roll”. The algorithm uses coevolution and exploits the distributed nature and symmetry of the tensegrity structure. We validate this algorithm using the NASA Tensegrity Robotics Toolkit (NTRT) simulator, as well as the highly accurate model of the physical SUPERBall being developped under the NASA Innovative and Advanced Concepts (NIAC) program. Flop and roll improves upon previous approaches in that it provides rolling to a desired location. It is also robust to both unexpected external forces and partial hardware failures. Additionally, it handles variable terrain (hills up to 33% grade). Finally, results are compatible with the hardware since the algorithm relies on realistic sensing and actuation capabilities of the SUPERBall.

State estimation for tensegrity robots

Tensegrity robots are a class of compliant robots that have many desirable traits when designing mass efficient systems that must interact with uncertain environments. Various promising control approaches have been proposed for tensegrity systems in simulation. Unfortunately, state estimation methods for tensegrity robots have not yet been thoroughly studied. In this paper, we present the design and evaluation of a state estimator for tensegrity robots. This state estimator will enable existing and future control algorithms to transfer from simulation to hardware. Our approach is based on the unscented Kalman filter (UKF) and combines inertial measurements, ultra wideband time-of-flight ranging measurements, and actuator state information. We evaluate the effectiveness of our method on the SUPERball, a tensegrity based planetary exploration robotic prototype. In particular, we conduct tests for evaluating both the robots success in estimating global position in relation to fixed ranging base stations during rolling maneuvers as well as local behavior due to small-amplitude deformations induced by cable actuation.

Development and field testing of the FootFall planning system for the ATHLETE robots

The FootFall Planning System is a ground-based planning and decision support system designed to facilitate the control of walking activities for the ATHLETE (All-Terrain Hex-Limbed Extra-Terrestrial Explorer) family of robots. ATHLETE was developed at NASAs Jet Propulsion Laboratory and is a large, six-legged robot designed to serve multiple roles during manned and unmanned missions to the moon; its roles include transportation, construction, and exploration. Over the 4 years from 2006 through 2010 the FootFall Planning System was developed and adapted to two generations of the ATHLETE robots and tested at two analog field sites [the Human Robotic Systems Projects Integrated Field Test at Moses Lake, Washington, June 2008, and the Desert Research and Technology Studies (D-RATS), held at Black Point Lava Flow in Arizona, September 2010]. Having 42 degrees of kinematic freedom, standing to a maximum height of just over 4 m, and having a payload capacity of 450 kg in Earth gravity, the current version of the ATHLETE robot is a uniquely complex system. A central challenge to this work was the compliance of the high-degree-of-freedom robot, especially the compliance of the wheels, which affected many aspects of statically stable walking. This paper reviews the history of the development of the FootFall system, sharing design decisions, field test experiences, and the lessons learned concerning compliance and self-awareness.

FootFall: A Ground Based Operations Toolset Enabling Walking for the ATHLETE Rover

The ATHLETE (All-Terrain Hex-Limbed Extra-Terrestrial Explorer) vehicle consists of six identical, six degree of freedom limbs. FootFall is a ground tool for ATHLETE intended to provide an operator with integrated situational awareness, terrain reconstruction, stability and safety analysis, motion planning, and decision support capabilities to enable the efficient generation of flight software command sequences for walking. FootFall has been under development at NASA Ames for the last year, and having accomplished the initial integration, it is being used to generate command sequences for single footfalls. In this paper, the architecture of FootFall in its current state will be presented, results from the recent Human Robotic Systems Project?s Integrated Field Test (Moses Lake, Washington, June, 2008) will be discussed, and future plans for extending the capabilities of FootFall to enable ATHLETE to walk across a boulder field in real time will be described.