Comparative Study of Different Methods in Vibration-Based Terrain Classification for Wheeled Robots with Shock Absorbers

open access articleAutonomous robots that operate in the field can enhance their security and efficiency by accurate terrain classification, which can be realized by means of robot-terrain interaction-generated vibration signals. In this paper, we explore the vibration-based terrain classification (VTC), in particular for a wheeled robot with shock absorbers. Because the vibration sensors are usually mounted on the main body of the robot, the vibration signals are dampened significantly, which results in the vibration signals collected on different terrains being more difficult to discriminate. Hence, the existing VTC methods applied to a robot with shock absorbers may degrade. The contributions are two-fold: (1) Several experiments are conducted to exhibit the performance of the existing feature-engineering and feature-learning classification methods; and (2) According to the long short-term memory (LSTM) network, we propose a one-dimensional convolutional LSTM (1DCL)-based VTC method to learn both spatial and temporal characteristics of the dampened vibration signals. The experiment results demonstrate that: (1) The feature-engineering methods, which are efficient in VTC of the robot without shock absorbers, are not so accurate in our project; meanwhile, the feature-learning methods are better choices; and (2) The 1DCL-based VTC method outperforms the conventional methods with an accuracy of 80.18%, which exceeds the second method (LSTM) by 8.23%

Planetary Cliff Descent Using Cooperative Robots

Future robotic planetary exploration will need to traverse geographically diverse and challenging terrain. Cliffs, ravines, and fissures are of great scientific interest because they may contain important data regarding past water flow and past life. Highly sloped terrain is difficult and often impossible to safely navigate using a single robot. This paper describes a control system for a team of three robots that access cliff walls at inclines up to 70°. Two robot assistants, or anchors, lower a third robot, called the rappeller, down the cliff using tethers. The anchors use actively controlled winches to first assist the rappeller in navigation about the cliff face and then retreat to safe ground. This paper describes the coordination of these three robots so they function as a team to explore the cliff face. Stability requirements for safe operation are identified and a behavior-based control scheme is presented. Behaviors are defined for the system and command fusion methods are described. Controller stability and sensitivity are examined. System performance is evaluated with simulation, a laboratory system, and testing in field environments

A concept study of small planetary rovers : using Tensegrity Structures on Venus

Venus is among the most enigmatic and interesting places to explore in the solar system. However, the surface of Venus is a very hostile, rocky environment with extreme temperatures, pressures, and chemical corrosivity. A planetary rover to explore the surface would be scientifically valuable, but must use unconventional methods in place of traditional robotic control and mobility. This study proposes that a tensegrity structure can provide adaptivity and control in place of a traditional mechanism and electronic controls for mobility on the surface of Venus and in other extreme environments. Tensegrity structures are light and compliant, being constructed from simple repeating rigid and flexible members and stabilized only by tension, drawing inspiration from biology and geometry, and are suitable for folding, deployment, and adaptability to terrain. They can also utilize properties of smart materials and geometry to achieve prescribed movements. Based on the needs of scientific exploration, a simple tensegrity rover can provide mobility and robustness to terrain and environmental conditions, and can be powered by environmental sources such as wind. A wide variety of tensegrity structures are possible, and some initial concepts suitable for volatile and complex environments are proposed here

Enhanced teleoperation interfaces for multi-second latency conditions: System design and evaluation

Adding human cognitive skills to planetary exploration through remote teleoperation can lead to more effective and valuable scientific data acquisition. Still, even small amounts of latency can significantly affect real-time operations, often leading to compromised robot safety, goal overshoot, and high levels of human mental fatigue and cognitive workload. Thus, novel operational strategies are necessary to cope with these effects. This paper proposes three augmented teleoperation interfaces that allow the user to operate a robot subject to 3 seconds of latency: (1) Avatar-Aided Interface (AAI), a semi-autonomous approach based on a virtual element; (2) Predictive Interface (PI), an approach with direct control and predictive elements; and (3) Hybrid Interface (HI), where the operator can easily switch between PI and AAI. We conducted a systematic within-subject experiment to evaluate the proposed interfaces in a realistic virtual environment with frequent traction losses. The user study compared AAI and PI to a Control Interface (CI), which did not display any augmented elements. The main results of this comparison showed that: (1) AAI led to a significant reduction in workload and a significant increase in usability and robot safety; (2) the use of the PI caused a significant increase in path length, indicating that operators overshoot their goals more often with this approach; (3) PI and AAI had lower reported effort; and (4) AAI is more flexible and effortless than PI and CI. Finally, the presented results show the need to consider uncertainty (e.g., traction loss) in future interface design.info:eu-repo/semantics/publishedVersio

Intelligence for Human-Assistant Planetary Surface Robots

The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area

Enabling All-Access Mobility for Planetary Exploration Vehicles via Transformative Reconfiguration

Effective large-scale exploration of planetary surfaces requires robotic vehicles capable of mobility across chaotic terrain. Characterized by a combination of ridges, cracks and valleys, the demands of this environment can cause spacecraft to experience significant reductions in operating footprint, performance, or even result in total system loss. Significantly increasing the scientific return of an interplanetary mission is facilitated by architectures capable of real-time configuration changes that go beyond that of active suspensions while concurrently meeting system, mass, power, and cost constraints. This Phase 1 report systematically explores how in-service architecture changes can expand system capabilities and mission opportunities. A foundation for concept generation is supplied by four Martian mission profiles spanning chasms, ice fields, craters and rocky terrain. A fifth mission profile centered on Near Earth Object exploration is also introduced. Concept generation is directed using four transformation principles - a taxonomy developed by the engineering design community to explain the cause of an architecture change and existing brainstorming techniques. This allowed early conceptual sketches of architecture changes to be organized by the principle driving the greatest increase in mission performance capability