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 NASA's Jet Propulsion Laboratory (JPL) 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 four 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 Project's 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 meters, 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-DOF (Degree Of Freedom) robot, especially the compliance of the wheels, which affected many aspects of statically-stable walking. This paper will review the history of the development of the FootFall system, sharing design decisions, field test experiences, and the lessons learned concerning compliance and self-awareness

Pressurized Lunar Rover

The pressurized lunar rover (PLR) consists of a 7 m long, 3 m diameter cylindrical main vehicle and a trailer which houses the power and heat rejection systems. The main vehicle carries the astronauts, life support systems, navigation and communication systems, directional lighting, cameras, and equipment for exploratory experiments. The PLR shell is constructed of a layered carbon-fiber/foam composite. The rover has six 1.5 m diameter wheels on the main body and two 1.5 m diameter wheels on the trailer. The wheels are constructed of composites and flex to increase traction and shock absorption. The wheels are each attached to a double A-arm aluminum suspension, which allows each wheel 1 m of vertical motion. In conjunction with a 0.75 m ground clearance, the suspension aids the rover in negotiating the uneven lunar terrain. The 15 N-m torque brushless electric motors are mounted with harmonic drive units inside each of the wheels. The rover is steered by electrically varying the speeds of the wheels on either side of the rover. The PLR trailer contains a radiosotope thermoelectric generator providing 6.7 kW. A secondary back-up energy storage system for short-term high-power needs is provided by a bank of batteries. The trailer can be detached to facilitate docking of the main body with the lunar base via an airlock located in the rear of the PLR. The airlock is also used for EVA operation during missions. Life support is a partly regenerative system with air and hygiene water being recycled. A layer of water inside the composite shell surrounds the command center. The water absorbs any damaging radiation, allowing the command center to be used as a safe haven during solar flares. Guidance, navigation, and control are supplied by a strapdown inertial measurement unit that works with the on-board computer. Star mappers provide periodic error correction. The PLR is capable of voice, video, and data transmission. It is equipped with two 5 W X-band transponder, allowing simultaneous transmission and reception. An S-band transponder is used to communicate with the crew during EVA. The PLR has a total mass of 6197 kg. It has a nominal speed of 10 km/hr and a top speed of 18 km/hr. The rover is capable of towing 3 metric tons (in addition to the RTG trailer)

The Lunar Roving Vehicle: Historical perspective

As NASA proceeds with its studies, planning, and technology efforts in preparing for the early twenty-first century, it seems appropriate to reexamine past programs for potential applicability in meeting future national space science and exploration goals and objectives. Both the National Commission on Space (NCOS) study and NASA's 'Sally Ride study' suggest future programs involving returning to the Moon and establishing man's permanent presence there, and/or visiting the planet Mars in both the unmanned and manned mode. Regardless of when and which of these new bold initiatives is selected as our next national space goal, implementing these potentially new national thrusts in space will undoubtedly require the use of both manned and remotely controlled roving vehicles. Therefore, the purpose of this paper is to raise the consciousness level of the current space exploration planners to what, in the early 1970s, was a highly successful roving vehicle. During the Apollo program the vehicle known as the Lunar Roving Vehicle (LRV) was designed for carrying two astronauts, their tools, and the equipment needed for rudimentary exploration of the Moon. This paper contains a discussion of the vehicle, its characteristics, and its use on the Moon. Conceivably, the LRV has the potential to meet some future requirements, either with relatively low cost modifications or via an evolutionary route. This aspect, however, is left to those who would choose to further study these options

Emergency preparedness for tunnel fires – A systems-oriented approach

Efficient emergency response is key to preventing major losses in tunnel fires. Our general concern in this paper is the degree to which tunnel systems are prepared and the means by which we can be prepared for a major fire in a single-tube road tunnel. Conformance to prescriptive regulations dominates existing practice in the area of emergency preparedness. Risk-based approaches exist but have little influence on emergency preparedness designs for tunnel systems. A successful emergency response to tunnel fires is dependent on many actors collaborating under serious time constraints. Safety becomes a matter of controlling critical processes necessary to keep the system in a safe state. Efficient decision-making in situations of major uncertainty is vital, to achieve safety goals. This essentially means that efficient emergency preparedness for road tunnels is a matter that needs attention in the early design phases and continuous improvements during the operational phase. To achieve high-performance emergency preparedness against tunnel fires, there is a need for radical changes to the design and operation of tunnels. In this paper, it is claimed that a system-theoretic approach is appropriate to deal with the tunnel system’s complexity and to drive the design of appropriate control structures for critical processes, from the design phase to the actual emergency. It is shown how system theoretic approaches will change the safety management practices for tunnels and how this will increase consistency between potential fire scenarios and associated control actions.publishedVersio

Project Lead The Way 2018 Program Booklet

Project Lead The Way 2018 Program Bookle

Symbiotic relationship between robots - a ROS ARDrone/YouBot library

A Symbiotic relationship between robots is theoretically developed. It is characterised by sharing sensory information and tightly coordinating operational logic by taking care of each other’s needs during missions. The system is characterised by an intertwined reasoning system while having separate conditioning and execution of plans to achieve subgoals to support each other. The results are illustrated on strong operational inter-dependence of a rover and a drone through shared logical inference. The drone uses the rover as a landing pad and the rover uses the drone to complements its sensor system by information gathering. There is a GitHub library provided in association with the demonstration for generic use of adding cameras and cooperation logic to a AR.Drone 2.0 and a KUKA youBot system. The benefits of symbiotic relationship are quantitatively evaluated on the demonstration example

A new Measure for Optimization of Field Sensor Network with Application to LiDAR

This thesis proposes a solution to the problem of modeling and optimizing the field sensor network in terms of the coverage performance. The term field sensor is referred to a class of sensors which can detect the regions in 2D/3D spaces through non-contact measurements. The most widely used field sensors include cameras, LiDAR, ultrasonic sensor, and RADAR, etc. The key challenge in the applications of field sensor networks, such as area coverage, is to develop an effective performance measure, which has to involve both sensor and environment parameters. The nature of space distribution in the case of the field sensor incurs a great deal of difficulties for such development and, hence, poses it as a very interesting research problem. Therefore, to tackle this problem, several attempts have been made in the literature. However, they have failed to address a comprehensive and applicable approach to distinctive types of field sensors (in 3D), as only coverage of a particular sensor is usually addressed at the time. In addition, no coverage model has been proposed yet for some types of field sensors such as LiDAR sensors. In this dissertation, a coverage model is obtained for the field sensors based on the transformation of sensor and task parameters into the sensor geometric model. By providing a mathematical description of the sensor’s sensing region, a performance measure is introduced which characterizes the closeness between a single sensor and target configurations. In this regard, the first contribution is developing an Infinity norm based measure which describes the target distance to the closure of the sensing region expressed by an area-based approach. The second contribution can be geometrically interpreted as mapping the sensor’s sensing region to an n-ball using a homeomorphism map and developing a performance measure. The third contribution is introducing the measurement principle and establishing the coverage model for the class of solid-state (flash) LiDAR sensors. The fourth contribution is point density analysis and developing the coverage model for the class of mechanical (prism rotating mechanism) LiDAR sensors. Finally, the effectiveness of the proposed coverage model is illustrated by simulations, experiments, and comparisons is carried out throughout the dissertation. This coverage model is a powerful tool as it applies to the variety of field sensors

Infrastructure Enabled Autonomy Acting as an Intelligent Transportation System for Autonomous Cars

Autonomous cars have the ability to increase safety, efficiency, and speed of travel. Yet many see a point at which stand-alone autonomous agents populate an area too densely, creating increased risk - particularly when each agent is operating and making decisions on its own and in its own self-interest. The problem at hand then becomes how to best implement and scale this new technology and structure in such a way that it can keep pace with a rapidly changing world, benefitting not just individuals, but societies. This research approaches the challenge by developing an intelligent transportation system that relies on an infrastructure. The solution lies in the removal of sensing and high computational tasks from the vehicles, allowing static ground stations with multi sensor-sensing packs to sense the surrounding environment and direct the vehicles safely from start to goal. On a high level, the Infrastructure Enabled Autonomy system (IEA) uses less hardware, bandwidth, energy, and money to maintain a controlled environment for a vehicle to operate when in highly congested environments. Through the development of background detection algorithms, this research has shown the advantage of static MSSPs analyzing the same environment over time, and carrying an increased reliability from fewer unknowns about the area of interest. It was determined through testing that wireless commands can sufficiently operate a vehicle in a limited agent environment, and do not bottleneck the system. The horizontal trial outcome illustrated that a switching MSSP state of the IEA system showed similar loop time, but a greatly increased standard deviation. However, after performing a t-test with a 95 percent confidence interval, the static and switching MSSP state trials were not significantly different. The final testing quantified the cross track error. For a straight path, the vehicle being controlled by the IEA system had a cross track error less than 12 centimeters, meaning between the controller, network lag, and pixel error, the system was robust enough to generate stable control of the vehicle with minimal error