Software toolkit for modeling,simulation, and control of soft robots

The technological differences between traditional robotics and soft robotics have an impact on all of the modeling tools generally in use, including direct kinematics and inverse models, Jacobians, and dynamics. Due to the lack of precise modeling and control methods for soft robots, the promising concepts of using such design for complex applications (medicine, assistance, domestic robotics, etc.) cannot be practically implemented. This paper presents a first unified software framework dedicated to modeling, simulation, and control of soft robots. The framework relies on continuum mechanics for modeling the robotic parts and boundary conditions like actuators and contacts using a unified representation based on Lagrange multipliers. It enables the digital robot to be simulated in its environment using a direct model. The model can also be inverted online using an optimization-based method which allows to control the physical robots in the task space. To demonstrate the effectiveness of the approach, we present various soft robots scenarios including ones where the robot is interacting with its environment. The software has been built on top of SOFA, an open-source framework for deformable online simulation and is available at https://project.inria.fr/softrobot/.     

Adequate motion simulation and collision detection for soccer playing humanoid robots

In this paper a humanoid robot simulator based on the multi-robot simulation framework (MuRoSimF) is presented. Among the unique features of this simulator is the scalability in the level of physical detail in both the robot’s motion and sensing systems. It facilitates the development of control software for humanoid robots which is demonstrated for several scenarios from the RoboCup Humanoid Robot League.Different requirements exist for a humanoid robot simulator. E.g., testing of algorithms for motion control and postural stability require high fidelity of physical motion properties whereas testing of behavior control and role distribution for a robot team requires only a moderate level of detail for real-time simulation of multiple robots. To meet such very different requirements often different simulators are used which makes it necessary to model a robot multiple times and to integrate different simulations with high-level robot control software.MuRoSimF provides the capability of exchanging the simulation algorithms used for each robot transparently, thus allowing a trade-off between computational performance and fidelity of the simulation. It is therefore possible to choose different simulation algorithms which are adequate for the needs of a given simulation experiment, for example, motion simulation of humanoid robots based on kinematical, simplified dynamics or full multi-body system dynamics algorithms. In this paper also the sensor simulation capabilities of MuRoSimF are revised. The methods for motion simulation and collision detection and handling are presented in detail including an algorithm which allows the real-time simulation of the full dynamics of a 21 DOF humanoid robot. Merits and drawbacks of the different algorithms are discussed in the light of different simulation purposes. The simulator performance is measured and illustrated in various examples, including comparison with experiments of a physical humanoid robot.     

Stability analysis of the internal dynamics of a wheeled mobile robot

The stability of the internal dynamics of a wheeled mobile robot is analyzed. It is shown that the wheeled mobile robot exhibits unstable internal dynamics when moving backwards. Most control methods of wheeled mobile robots are designed based on input-output relations. Since the internal dynamics are not represented in input-output relations, stability properties of the internal dynamics are generally neglected. Nevertheless, the internal dynamics do affect the behavior of mobile robots. Taking the look-ahead control method as an example, it is shown that, by using a novel Liapunov function, the internal dynamics of a two-wheel differential-drive mobile robot are unstable when it is commanded to move backwards. Both simulation and experimental results are provided to verify the analysis. ©1997 John Wiley & Sons, Inc.     

Robots in space - a survey

The paper tries to outline the state of the art in space robotics. It discusses the technologies used in ROTEX, the first remotely controlled space robot which flew with the shuttle Columbia in April 1993, but it also gives a review of the major space robot projects envisioned by different nations for the next decade. The mechatronics and dynamics aspects of space robots including free-flying systems are briefly discussed. Broader attention is given to the telerobotic and teleoperational control loop structures, including predictive delay-compensating graphics simulation. The paper finally tries to emphasize that by task-level programming (involving 'learning by showing' on a high level) future space robots will be powerful tools for scientists and ground operators which are not robot specialists. The tele-sensor programming concept of ROTEX was a first step in this direction. We plead for flying a variety of space robot systems in the near future in order to enhance experience with and confidence in these technologies as quickly as possible.     

A methodology for design and analysis of cooperative behaviors with mobile robots

New methodologies are needed for modeling of physically cooperating mobile robots to be able to systematically design and analyze such systems. In this context, we present a method called the ‘P-robot Method’ under which we introduce entities called the p-robots at the environmental contact points and treat the linked mobile robots as a multiple degree-of-freedom object, comprising an articulated open kinematic chain, which is manipulated by the p-robots. The method is suitable to address three critical aspects of physical cooperation: a) analysis of environmental contacts, b) utilization of redundancy, and c) exploitation of system dynamics. Dynamics of the open chain are computed independent of the constraints, thus allowing the same set of equations to be used as the constraint conditions change, and simplifying the addition of multiple robots to the chain. The decoupling achieved through constraining the p-robots facilitates the analysis of kinematic as well as force constraints. We introduce the idea of a ‘tipping cone’, similar to a standard friction cone, to test whether forces on the robots cause undesired tipping. We have employed the P-robot Method for the static as well as dynamic analysis for a cooperative behavior involving two robots. The method is generalizable to analyze cooperative behaviors with any number of robots. We demonstrate that redundant actuation achieved by an adding a third robot to cooperation can help in satisfying the contact constraints. The P-robot Method can be useful to analyze other interesting multi-body robotic systems as well.     

Visual task identification and characterization using polynomial models

Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predict robot behaviour based on theoretical models. Instead, current methods to develop robot control code still require a substantial trial-and-error component to the software design process.This paper proposes a method of dealing with these issues by (a) establishing task-achieving sensor-motor couplings through robot training, and (b) representing these couplings through transparent mathematical functions that can be used to form hypotheses and theoretical analyses of robot behaviour.We demonstrate the viability of this approach by teaching a mobile robot to track a moving football and subsequently modelling this task using the NARMAX system identification technique.     

A real-time,high fidelity dynamic simulation platform for hexapod robots on soft terrain

Dynamic simulation is an important aspect of legged robotic research, which is essential for its design and control. However, the dynamics of the interaction between a soft terrain and a deformable leg (e.g., a spring) is hardly taken into account. In this paper, a high-fidelity, faster-than-real-time simulation system for hexapod robots has been developed based on Vortex. Foot-terrain interaction mechanics and flexible mechanical system are taken into account in order to improve the simulation precision. A general foot-terrain interaction model is presented based on terramechanics. Pseudo-rigid-body method is used to simulate the flexibility of the robot. A speed test shows that the simulation system is capable of real-time or faster simulation. The simulation system's fidelity was validated using two hexapod robots, which is found to be greater than 90%.     

Evolving reliable and robust controllers for real robots by genetic programming

 Using Genetic Programming (GP)-based approaches to evolve robot controllers has the advantage of operating variable-size genotype. This is an important feature for evolving robot control systems as it allows complete freedom for the control architecture in respect to the task complexity which is difficult to predict. However, GP-based work in evolving controllers has been questioned in the verification of the performance on real robots, the generalisation of defining primitives, and the computational cost needed. In this paper, we present our GP framework in which a special representation of the robot controller is designed; this representation can capture well the characteristic of a behaviour controller so that our system can efficiently evolve desired robot behaviours by a relatively low computational cost. This system has been successfully used to evolve reliable and robust controllers working on a real robot, for a variety of tasks.     

Behaviors for physical cooperation between robots for mobility improvement

A team of small, low-cost robots instead of a single large, complex robot is useful in operations such as search and rescue, urban exploration etc. However, performance of such a team is limited due to restricted mobility of the team members. We propose solutions based on physical cooperation among mobile robots to improve the overall mobility. Our focus is on the development of the low level system components. Recognizing that small robots need to overcome discrete obstacles, we develop specific analytical maneuvers to negotiate each obstacle where a maneuver is built from a sequence of fundamental cooperative behaviors. In this paper we present cooperative behaviors that are achieved by interactions among robots via un-actuated links thus avoiding the need for additional actuation. We analyze the cooperative lift behavior and demonstrate that useful maneuvers such a gap crossing can be built using this behavior. We prove that the requirements on ground friction and wheel torques set fundamental limits for physical cooperation. Using the design guidelines based on static analysis we have developed simple and low cost hardware to illustrate cooperative gap crossing with two robots. We have developed a complete dynamic model of two-robot cooperation which leads to control design. A novel connecting link design is proposed that can change the system configuration with no additional actuators. A decentralized control architecture is designed for the two-robot system, where each robot controls its own state with no information about the state of the other robot thus avoiding the need of continuous communication between the two robots. Simulation and hardware results demonstrate a successful implementation with the gap crossing example. We have analytically proved that robot dynamics can be used to reduce the friction requirements and have demonstrated, with simulations, the implementation of this idea for the cooperative lifting behavior.

Using robots to model animals: a cricket test

The sensorimotor problems faced by animals and by robots have much in common, yet identifying this similarity has so far led to very few successful attempts to implement specific biological neural control structures on robots. One major limitation is that understanding of the biological mechanisms is insufficient for straightforward installation. However, using robots as a method of physically modeling animal systems can potentially contribute to our understanding of these mechanisms. This approach is employed in an investigation of phonotaxis (sound-seeking) in crickets. The process of building a robot forms the basis of a critical evaluation of the neuroethological evidence about the cricket, and generates an alternative hypothesis to explain this evidence. The explanatory power of this hypothesis is explored by testing and analyzing the behaviour of the robot that embodies it. The robot behaved like the cricket, competently and robustly finding its way to a specific sound source under a variety of conditions. It is argued that the methodology is more appropriate than symbolic simulation for the kinds of problems raised in the investigation of sensorimotor behaviour in animals and robots.     

Virtual manipulator-based binocular stereo vision positioning system and errors modelling

There is a bottleneck of mobile robots positioning technologies for uncertain goals in complex field environment. Owing to the disturbance of the environment, the objects are hard to be located precisely by robot manipulator. Aiming at the positioning problem, binocular stereo vision system and positioning principle of the picking manipulator in virtual environment (VE) were proposed and expatiated upon; in addition, the manipulator positioning model was built in VE, and the manipulator positioning simulation system was developed by Microsoft Visual C++ 6.0; and the binocular stereo vision system platform with a three-coordinate guideway positioning was constructed for test; what’s more the error sources of vision positioning system was analyzed, and the camera system error was established; the mathematical model of experimental error and the camera calibration matching error were also found; with the developed robot manipulator positioning simulation software and vision system hardware, an experimental platform of positioning system was constructed, and using the platform, the stereo vision data was mapped to the manipulator and was guiding the accurate positioning in VE. Finally, experiment of positioning error compensation was carried out. Results of simulation in VE and the experiment showed that the vision positioning method was feasible for positioning in the field environment; it can be applied to control robot operation and to correct the positioning errors in real-time, especially to the long-range precision modelling and error compensation of robots.     

Brains,Bodies, and Beyond: Competitive Co-Evolution of Robot Controllers,Morphologies and Environments

This paper presents a series of simulation experiments that incrementally extend previous work on neural robot controllers in a predator-prey scenario, in particular the work of Floreano and Nolfi, and integrates it with ideas from work on the ‘co-evolution’ of robot morphologies and control systems. The aim of these experiments has been to further systematically investigate the tradeoffs and interdependencies between morphological parameters and behavioral strategies through a series of predator-prey experiments in which increasingly many aspects are subject to self-organization through competitive co-evolution. Motivated by the fact that, despite the emphasis of the interdependence of brain, body and environment in much recent research, the environment has actually received relatively little attention, the last set of experiments lets robots/species actively adapt their environments to their own needs, rather than just adapting themselves to a given environment. This paper is an extended version of: Buason and Ziemke. “Co-evolving task-dependent visual morphologies in predator-prey experiments,” in Genetic and Evolutionary Computation Conference, Cantu-Paz et al. (Eds.), Springer Verlag: Berlin, 2003, pp. 458–469.     

Degradation curves integration in physics-based models: Towards the predictive maintenance of industrial robots

Predictive maintenance has been proposed to maximize the overall plant availability of modern manufacturing systems. To this end, research has been conducted mainly on data-driven prognostic techniques for machinery equipment individual components. However, the lack of historical data together with the intricate design of industrial machines, e.g. robots, stimulate the use of advanced methods exploiting simulation capabilities. This paper aims to address this challenge by introducing a generic framework for the enhancement of advanced physics-based models with degradation curves. The creation of a robot's simulation model and its enrichment with data from the degradation curves of the robot's components is presented. Following, the extraction of information from degradation curves during the simulation of the robot's dynamic behaviour is addressed. The Digital Twin concept is employed to monitor the health status of the robot and ensure the convergence of the simulated to the actual robot behaviour. The output of the simulation can enable to estimate the future behaviour of the robot and make predictions for the quality of the products to be produced, as well as to estimate the robot's Remaining Useful Life. The proposed approach is applied in a case study coming from the white goods industry, where it is investigated whether the robot will experience some failure within the next 18 months.     

Multiagent-Based Multi-team Formation Control for Mobile Robots

In the field of formation control, researchers generally control multiple robots in only one team, and little research focuses on multi-team formation control. In this paper, we propose an architecture, called Virtual Operator MultiAgent System (VOMAS), to perform formation control for multiple teams of mobile robots with the capabilities and advantages of scalability and autonomy. VOMAS is a hybrid architecture with two main agents. The virtual operator agent handles high level missions and team control, and the robot agent deals with low level formation control. The virtual operator uses four basic services including join, remove, split, and merge requests to perform multi-team control. A new robot can be easily added to a team by cloning a new virtual operator to control it. The robot agent uses a simple formation representation method to show formation to a large number of robots, and it uses the concept of potential field and behavior-based control to perform kinematic control to keep formation both in holonomic and nonholonomic mobile robots. In addition, we also test the stability, robustness, and uncertainty in the simulation. This research was supported by the National Science Council under grant NSC 91-2213-E-194-003.     

Hybrid autonomous control for multi mobile robots

Reinforcement learning can be an adaptive and flexible control method for autonomous system. It does not need a priori knowledge; behaviors to accomplish given tasks are obtained automatically by repeating trial and error. However, with increasing complexity of the system, the learning costs are increased exponentially. Thus, application to complex systems, like a many redundant d.o.f. robot and multi-agent system, is very difficult. In the previous works in this field, applications were restricted to simple robots and small multi-agent systems, and because of restricted functions of the simple systems that have less redundancy, effectiveness of reinforcement learning is restricted. In our previous works, we had taken these problems into consideration and had proposed new reinforcement learning algorithm, 'Q-learning with dynamic structuring of exploration space based on GA (QDSEGA)'. Effectiveness of QDSEGA for redundant robots has been demonstrated using a 12-legged robot and a 50-link manipulator. However, previous works on QDSEGA were restricted to redundant robots and it was impossible to apply it to multi mobile robots. In this paper, we extend our previous work on QDSEGA by combining a rule-based distributed control and propose a hybrid autonomous control method for multi mobile robots. To demonstrate the effectiveness of the proposed method, simulations of a transportation task by 10 mobile robots are carried out. As a result, effective behaviors have been obtained.     

Robots, insects and swarm intelligence

The aim of this paper is to consider the relationships between robots and insects. To this end, an overview is provided of the two main areas in which insects have been implicated in robotics research. First, robots have been used to provide working models of mechanisms underlying insect behaviour. Second, there are developments in robotics that have been inspired by our understanding of insect behaviour; in particular the approach of swarm robotics. In the final section of the paper, the possibility of achieving “strong swarm intelligence” is discussed. Two possible interpretations of strong swarm intelligence are raised: (1) the emergence of a group mind from a natural, or robot swarm, and (2) that behaviours could emerge from a swarm of artificial robots in the same way as they emerge from a biological swarm. Both interpretations are dismissed as being unachievable in principle. It is concluded that bio-robotic modelling and biological inspiration have made important contributions to both insect and robot research, but insects and robots remain separated by the divide between the living and the purely mechanical.     

Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging

Swarm robotics studies the intelligent collective behaviour emerging from long-term interactions of large number of simple robots. However, maintaining a large number of robots operational for long time periods requires significant battery capacity, which is an issue for small robots. Therefore, re-charging systems such as automated battery-swapping stations have been implemented. These systems require that the robots interrupt, albeit shortly, their activity, which influences the swarm behaviour. In this paper, a low-cost on-the-fly wireless charging system, composed of several charging cells, is proposed for use in swarm robotic research studies. To determine the system’s ability to support perpetual swarm operation, a probabilistic model that takes into account the swarm size, robot behaviour and charging area configuration, is outlined. Based on the model, a prototype system with 12 charging cells and a small mobile robot, Mona, was developed. A series of long-term experiments with different arenas and behavioural configurations indicated the model’s accuracy and demonstrated the system’s ability to support perpetual operation of multi-robotic system.