In this paper, we present the 2013 Response Robotics Summer School, an event for the dissemination of the challenges and Best-in-Class capabilities in response robotics, focusing on explosive ordnance disposal and remote handling. A particularly unique feature of this event was the close integration of the responder community in both the technical and practical sessions. This was made possible by co-locating and jointly running this event with the Bomb Response Technology Seminar, an annual workshop for civilian and military bomb squad personnel. This event also builds on a decade-long legacy of response robotics dissemination events. These events leverage the DHS-NIST-ASTM International Standard Test Methods for Response Robots as a common language with which responders, researchers, industry, students and test administrators may communicate their requirements, capabilities and motivations. It builds on the 2012 IEEE-RAS Safety, Security and Rescue Robotics Summer School and sets the stage for the 2014 IEEERAS Response Robotics Summer School.

Legged robots are by nature strongly non-linear, high-dimensional systems whose full complexity permits neither tractable mathematical analysis nor comprehensive numerical study. In consequence, a growing body of literature interrogates simplified "template" (Full and Koditschek, 1999; Ghigliazza et al., 2005) models - to date almost exclusively confined to sagittal- or horizontal-plane motion - with the aim of gaining insight into the design or control of the far messier reality. In this paper we introduce a simple bounding-in-place ("BIP") model as a candidate frontal plane template for straight-ahead level ground running and explore its use in formulating hypotheses about whether and why rolling motion is important in legged locomotion. Numerical study of left-right compliance asymmetry in the BIP model suggests that compliance ratios yielding lowest steady state roll suffer far longer disturbance recovery transients than those promoting greater steady state roll. We offer preliminary experimental data obtained from video motion capture data of the frontal plane disturbance recovery patterns of a RHex-like hexapod suggesting a correspondence to the conclusions of the numerical study.

We report on a hybrid 12-dimensional full body state estimator for a hexapod robot executing a jogging gait in steady state on level terrain with regularly alternating ground contact and aerial phases of motion. We use a repeating sequence of continuous time dynamical models that are switched in and out of an extended Kalman filter to fuse measurements from a novel leg pose sensor and inertial sensors. Our inertial measurement unit supplements the traditionally paired three-axis rate gyro and three-axis accelerometer with a set of three additional three-axis accelerometer suites, thereby providing additional angular acceleration measurement, avoiding the need for localization of the accelerometer at the center of mass on the robot's body, and simplifying installation and calibration. We implement this estimation procedure offline, using data extracted from numerous repeated runs of the hexapod robot RHex (bearing the appropriate sensor suite) and evaluate its performance with reference to a visual ground-truth measurement system, comparing as well the relative performance of different fusion approaches implemented via different model sequences

We report on progress toward a continuous time full 6 DOF translational body state estimator for a hexapod robot executing a jogging gait (with 4 consecutive phases: tripod stance, liftoff transient, aerial, and touchdown transient) on level ground. We use a sequence of dynamical models imported into a standard Kalman Filter to fuse measurements from a novel leg pose sensor and a conventional inertial measurement unit. We implement this estimation procedure on the hexapod robot RHex and evaluate its performance using a visual ground truth measurement system. We also compare the relative performance of different fusion approaches implemented via different model sequences.

We report on a continuous-time rigid-body pose estimator for a walking hexapod robot. Assuming at least three legs remain in ground contact at all times, our algorithm uses the outputs of six leg-configuration sensor models together with a priori knowledge of the ground and robot kinematics to compute instantaneous estimates of the 6-degrees-of-freedom (6-DOF) body pose. We implement this estimation procedure on the robot RHex by means of a novel sensory system incorporating a model relating compliant leg member strain to leg configuration delivered to the onboard CPU over a customized cheap high-performance local wireless network. We evaluate the performance of this algorithm at widely varying body speeds and over dramatically different ground conditions by means of a 6-DOF vision-based ground-truth measurement system (GTMS). We also compare the odometry performance to that of sensorless schemes - both legged as well as on a wheeled version of the robot - using GTMS measurements of elapsed distance.

We report on a continuous time full body state estimator for a hexapod robot operating in the dynamical regime (entailing a significant aerial phase) on level ground that combines a conventional rate gyro with a novel leg strain based body pose estimator. We implement this estimation procedure on the robot RHex and evaluate its performance using a visual ground truth measurement system. As an independent assessment of our estimator's quality we also compare its odometry performance to sensorless averaged open loop distance-per-stride estimates.

We report on a novel leg strain sensory system for the autonomous robot RHex [Saranli U. et al., 2001] implemented upon a cheap, high performance local wireless network [H. Komsuoglu, 2002]. We introduce a model for RHex's 4-bar legs [E.Z. Moore, 2001] relating leg strain to leg kinematic configuration in the body coordinate frame. We compare against ground truth measurement the performance of the model operating on real-time leg strain data generated under completely realistic operating conditions. We introduce an algorithm for computing six degree of freedom body posture measurements in world frame coordinates from the outputs of the six leg configuration models, together with a priori information about the ground. We discuss the manner in which such stance phase configuration estimates will be fused with other sensory data to develop the continuous time full body state estimates for RHex.

We report on our progress in extending the behavioral repertoire of RHex, a compliant leg hexapod robot. We introduce two new controllers, one for climbing constant slope inclinations and one for achieving higher speeds via pronking, a gait that incorporates a, substantial aerial phase. In both cases, we make use of an underlying open-loop control strategy, combined with low bandwidth feedback to modulate its parameters. The inclination behavior arises from our initial alternating tripod walking controller and adjusts the angle offsets of individual leg motion profiles based on inertial sensing of the average surface slope. Similarly, the pronking controller makes use of a "virtual" leg touchdown sensing mechanism to adjust the frequency of the open-loop pronking, effectively synchronizing the controller with the natural oscillations of the mechanical system. Experimental results demonstrate good performance on slopes inclined up to /spl sim/250 and pronking up to speeds approaching 2 body lengths per second (/spl sim/1.0 m/s).