Back Flips with a Hexapedal Robot

We report on the design and analysis of a controller which can achieve dynamical self-righting of our hexapedal robot, RHex. We present an empirically developed control procedure which works reasonably well on indoor surfaces, using a hybrid energy pumping strategy to overcome torque limitations of its actuators. Subsequent modeling and analysis yields a new controller with a much wider domain of success as well as a preliminary understanding of the necessary hybrid control strategy. Simulation results demonstrate the superiority of the improved control strategy to the first generation empirically designed controller

Extending The Lossy Spring-Loaded Inverted Pendulum Model with a Slider-Crank Mechanism

Spring Loaded Inverted Pendulum (SLIP) model has a long history in describing running behavior in animals and humans as well as has been used as a design basis for robots capable of dynamic locomotion. Anchoring the SLIP for lossy physical systems resulted in newer models which are extended versions of original SLIP with viscous damping in the leg. However, such lossy models require an additional mechanism for pumping energy to the system to control the locomotion and to reach a limit-cycle. Some studies solved this problem by adding an actively controllable torque actuation at the hip joint and this actuation has been successively used in many robotic platforms, such as the popular RHex robot. However, hip torque actuation produces forces on the COM dominantly at forward direction with respect to ground, making height control challenging especially at slow speeds. The situation becomes more severe when the horizontal speed of the robot reaches zero, i.e. steady hoping without moving in horizontal direction, and the system reaches to singularity in which vertical degrees of freedom is completely lost. To this end, we propose an extension of the lossy SLIP model with a slider-crank mechanism, SLIP- SCM, that can generate a stable limit-cycle when the body is constrained to vertical direction. We propose an approximate analytical solution to the nonlinear system dynamics of SLIP- SCM model to characterize its behavior during the locomotion. Finally, we perform a fixed-point stability analysis on SLIP-SCM model using our approximate analytical solution and show that proposed model exhibits stable behavior in our range of interest.Comment: To appear in The 17th International Conference on Advanced Robotic

A Real-time Inertial Motion Blur Metric: Application to Frame Triggering Based Motion Blur Minimization

Mobile robots suffer from sensory data corruption due to body oscillations and disturbances. In particular, information loss on images captured with onboard cameras can be very high, and such loss may become irreversible or computationally costly to undo. In this paper, we propose a novel method to minimize average motion blur captured by such mobile visual sensors. To this end, we derive a motion blur metric (MMBM) that can be computed in real-time by using only inertial sensor measurements and validate it through comparisons with optic flow computations. The applicability of MMBM is illustrated through a motion blur minimizing system implemented on the SensoRHex hexapod robot by externally triggering an onboard camera based on MMBM values computed in real-time while the robot is walking straight on a flat surface. The resulting motion blur is compared to motion blur levels obtained with a regular, fixed frame-rate image acquisition schedule by both qualitative inspection and using a blind blur metric on captured images. MMBM based motion blur minimization system not only reduces average motion blur, but also avoids frames with extreme motion blur before an image gets corrupted by appropriately delaying the triggering of frame acquisition

Template Based Control of Hexapedal Running

In this paper, we introduce a hexapedal locomotion controller that simulation evidence suggests will be capable of driving our RHex robot at speeds exceeding five body lengths per second with reliable stability and rapid maneuverability. We use a low dimensional passively compliant biped as a template -- a control target for the alternating tripod gait of the physical machine. We impose upon the physical machine an approrimate inverse dynamics within-stride controller designed to force the true high dimensional system dynamics down onto the lower dimensional subspace corresponding to the template. Numerical simulations suggest the presence of asymptotically stable mnning gaits with large basins of attraction. Moreover, this controller improves substantially the maneuverability and dynamic range of RHex\u27s running behaviors relative to the initial prototype open-loop algorithms

Experimental Validation of a Feed-Forward Predictor for the Spring-Loaded Inverted Pendulum Template

Cataloged from PDF version of article.Widely accepted utility of simple spring-mass models for running behaviors as descriptive tools, as well as literal control targets, motivates accurate analytical approximations to their dynamics. Despite the availability of a number of such analytical predictors in the literature, their validation has mostly been done in simulation, and it is yet unclear how well they perform when applied to physical platforms. In this paper, we extend on one of the most recent approximations in the literature to ensure its accuracy and applicability to a physical monopedal platform. To this end, we present systematic experiments on a well-instrumented planar monopod robot, first to perform careful identification of system parameters and subsequently to assess predictor performance. Our results show that the approximate solutions to the spring-loaded inverted pendulum dynamics are capable of predicting physical robot position and velocity trajectories with average prediction errors of 2% and 7%, respectively. This predictive performance together with the simple analytic nature of the approximations shows their suitability as a basis for both state estimators and locomotion controllers. © 2004-2012 IEEE

A Real-time Inertial Motion Blur Metric

Mobile robots suffer from sensor data corruption due to body oscillations and disturbances. Especially, information loss on images captured with onboard cameras can be extremely high and such loss may become irreversible or deblurring can be computationally costly. In this paper, a novel method is proposed to minimize average motion blur captured by mobile cameras. A real-time computable motion blur metric (MMBM) is derived by using only inertial sensor measurements. MMBM is validated by comparing it to optic flow results. To express the applicability of MMBM, a motion blur minimizing system is built on the RHex. To this end, an onboard camera is externally triggered depending on the real-time-calculated MMBM while the robot is walking straight on a flat surface. The resulting motion blur is compared to motion blur levels of a regular, fixed frame-rate image acquisition schedule by qualitative inspection on captured images

A Cross-Cultural Perspective about the Implementation and Adaptation Process of the Schoolwide Enrichment Model

Gifted education and talent development are considered today as key elements for developing human capital and increasing competitiveness within education and the economy. Within this framework, a growing number of countries have begun to invest large amounts of resources to discover and nurture their most able students. As boundaries and differences between cultures become less pronounced in a global world, educational models to guide gifted education and talent development are also becoming more widely applicable. In this context, the Schoolwide Enrichment Model (SEM) stands as a flexible model that enables schools in different regions of the world to provide individuals with opportunities to identify their potentials and to help them reach their highest levels of competence. This paper provides an overview of the SEM and the broad range of regions in which the model is currently implemented, as well as an examination of the reasons for its widespread acceptance among educators around the world. In addition, this paper includes an interview with Dr Joseph Renzulli, inventor of SEM, in which several issues related to the cultural adaptation of the SEM are discussed. Finally, the paper presents an introduction to the SEM International Network, a newly developed project created to connect SEM users around the world and to facilitate the sharing and accessing of ideas and resources for talent development

A Modular, Real-Time Fieldbus Architecture for Mobile Robotic Platforms

Cataloged from PDF version of article.The design and construction of complex and reconfigurable embedded systems such as small autonomous mobile robots is a challenging task that involves the selection, interfacing, and programming of a large number of sensors and actuators. Facilitating this tedious process requires modularity and extensibility both in hardware and software components. In this paper, we introduce the universal robot bus (URB), a real-time fieldbus architecture that facilitates rapid integration of heterogeneous sensor and actuator nodes to a central processing unit (CPU) while providing a software abstraction that eliminates complications arising from the lack of hardware homogeneity. Motivated by our primary application area of mobile robotics, URB is designed to be very lightweight and efficient, with real-time support for Recommended Standard (RS) 232 or universal serial bus connections to a central computer and inter-integrated circuit (I(2)C), controller area network, or RS485 bus connections to embedded nodes. It supports automatic synchronization of data acquisition across multiple nodes, provides high data bandwidth at low deterministic latencies, and includes flexible libraries for modular software development both for local nodes and the CPU. This paper describes the design of the URB architecture, provides a careful experimental characterization of its performance, and demonstrates its utility in the context of its deployment in a legged robot platform

Multi-point Contact Models for Dynamic Self-Righting of a Hexapod Robot

In this paper, we report on the design of a model-based controller that can achieve dynamical self-righting of a hexapod robot. Extending on our earlier work in this domain, we introduce a tractable multi-point contact model with Coulomb friction. We contrast the singularities inherent to the new model with other available methods and show that for our specific application, it yields dynamics which are well-defined. We then present a feedback controller that achieves “maximal” performance under morphological and actuation constraints, while ensuring the validity of the model by staying away from singularities. Finally, through systematic experiments, we demonstrate that our controller is capable of robust flipping behavior. For more information: Kod*La

Model-Based Dynamic Self-Righting Maneuvers for a Hexapedal Robot

We report on the design and analysis of a controller that can achieve dynamical self-righting of our hexapedal robot, RHex. Motivated by the initial success of an empirically tuned controller, we present a feedback controller based on a saggital plane model of the robot. We also extend this controller to develop a hybrid pumping strategy that overcomes actuator torque limitations, resulting in robust flipping behavior over a wide range of surfaces. We present simulations and experiments to validate the model and characterize the performance of the new controller