Exploratory Robots Research Articles

A Study for Comparative Analysis of Dueling DQN and Centralized Critic Approaches in Multi-Agent Reinforcement Learning

In this study, we introduce a deep Q-network agent utilizing a dueling architecture to refine the valuation of actions through separate estimations of the state-value and action-value functions, adapted to facilitate concurrent multi-agent operations within a shared environment. Inspired by the self-organized, decentralized cooperation observed in natural swarms, this study uniquely integrates a centralized mechanism, or a centralized critic. This enhances performance and coherence in decision-making within the multi-agent system. This hybrid approach enables agents to execute informed and optimized decisions by considering the actions of their counterparts while maintaining an element of collective and flexible task-information sharing, thereby presenting a groundbreaking framework for cooperation and information sharing in swarm robot systems. To augment the communication capabilities, we employ low-power wide-area networks, or Long Range (LoRa), which are characterized by their low power consumption and long-range communication abilities, facilitating the sharing of task information and reducing the load on individual robots. The aim is to leverage LoRa as a communication platform to construct a cooperative algorithm that enables efficient task-information sharing among groups. This can provide innovative solutions and promote effective cooperation and communication within multi-agent systems, with significant implications for industrial and exploratory robots. In conclusion, by integrating a centralized system into the proposed model, this approach successfully enhances the performance of multi-agent systems in real-world applications, offering a balanced synergy between decentralized flexibility and centralized control.

Golden wheel spider-inspired rolling robots for planetary exploration

Humans have been fascinated with nature and attempting to mimic what they see in nature for millennia. Using inspiration from organisms found in nature assists in developing a system that is well-suited for specific tasks and environments. This process is called bio-inspiration. When designing bio-inspired robots, locomotion is one of the most common sources of inspiration. Exploratory robots are often limited to wheels as the mode of transportation, but there are so many more options, each with its own benefits and uses. This work focuses on the design and development of various rolling robots for planetary exploration. Specifically, these rolling robots are being designed for the exploration of the Martian surface. The main source of inspiration for these rovers is the Golden Wheel Spider. This spider is known for its wind-assisted rolling capabilities, allowing it to traverse sand dunes with minimal effort quickly. In addition to prototypes, a dynamical model of the conceptual Spider Rolling Robot (SRR) has been developed. Studies have been done to determine just how much the wind will be able to assist the SRR under realistic conditions on the Martian surface. Finally, CoppeliaSim simulations have been built to test and compare various model designs to find the most effective form of the SRR.

Waterproof Design of Soft Multi-Directional Force Sensor for Underwater Robotic Applications

Directional force sensing is an intrinsic feature of tactile sensing. As technologies of exploratory robots evolve, with special emphasis on the emergence of soft robotics, it is crucial to equip robotic end-effectors with effective means of characterizing trends in force detection and grasping phenomena, while these trends are largely derived from networks of tactile sensors working together, individual sensors must be built to meet an intended function and maintain functionality with respect to environmental operating conditions. The harshness of underwater exploration imposes a unique set of circumstances onto the design of tactile sensors. When exposed to underwater conditions a tactile sensor must be able to withstand the effects of increased pressure paired with water intrusion while maintaining computational and mechanical integrity. Robotic systems designed for the underwater environment often become expensive and cumbersome. This paper presents the design, fabrication, and performance of a low-cost, soft-material sensor capable of multi-directional force detection. The fundamental design consists of four piezo-resistive flex elements offset at 90∘ increments and encased inside of a hemispherical silicone membrane filled with a non-compressive and non-conductive fluid. The sensor is simulated numerically to characterize soft-material deformation and is experimentally interrogated with indentation equipment to investigate sensor-data patterns when subject to different contact forces. Furthermore, the sensor is subject to a cyclic loading test to analyze the effects of hysteresis in the silicone and is submerged underwater for a 7-day period to investigate any effect of water intrusion at a shallow depth. The outcome of this paper is the proposed design of a waterproofed, soft-material tactile sensor capable of directional force detection and contact force localization. The overall goal is to widen the scope of tactile sensor concepts outfitted for the underwater environment.

Multi-Objective Optimal Path Planning for Autonomous Robots with Moving Obstacles Avoidance in Dynamic Environments

Path planning is vital for robust autonomous robot navigation. Driving in dynamic environments is particularly difficult. The majority of the work is based on the premise that a robot possesses a comprehensive and precise representation of its surroundings prior to its starting. The problem of partially knowing and dynamic environments has received little attention. This circumstance occurs when an exploratory robot or a robot without a floor plan or terrain map must move to its destination. Existing approaches for dynamic-path-planning design a preliminary path based-on known knowledge of the environment, then adjust locally by replanning the total path as obstacles are discovered by the robot's sensors, thereby sacrificing either optimality or computational efficacy. This paper presents a novel algorithm. A Near-Optimal Multi-Objective Path Planner (NO-MOPP), capable of planning time-efficient, near-optimal, and drivable paths in partially known and dynamic environments. It is an expansion of our earlier research contributions called "A Multi-Objective Hybrid Collision-free Optimal Path Finder (MOHC-OPF) for Autonomous Robots in known static environments" and "A Multi-Objective Hybrid Collision-free Near-Optimal Path Planner (MOHC-NODPP) for Autonomous Robots in Dynamic environments". In the environment, a mix of static and moving dynamic obstacles are present, both of which are expressed by a hybrid, discrete configuration space in an occupancy-grid map. The proposed approach is executed at two distinct levels. Using our earlier method, A Multi-Objective Collision-free Optimal Path Finder (MOHC-OPF), the initial optimal path is found in environment that includes only known stationery obstacles at the Global-path-planning level. On the second level, known as Local Re-planning, this optimal path is continuously refined by online re-planning to account for the movement of obstacles in the environment. The proposed method, A Near-Optimal Multi-Objective Path Planner (NO-MOPP), is used to keep the robot's sub-paths optimum while also avoiding dynamic obstacles. This is done while still obeying the robot's non-holonomic restrictions. The proposed technique is tested in simulation using a collection of standard maps. The simulation findings demonstrate the proposed method's ability to avoid static as well as dynamic obstacles, as well as its capacity to find a near-optimal-path to a goal location in environments that are constantly changing without collision. The optimal-path is determined by taking into account several performance measures, including path length, collision-free path, execution time, and smooth paths. 90% of studies utilizing the proposed method demonstrate that it is more effective than other methods for determining the shortest length and time-efficient smooth drivable paths. The proposed technique reduced average 15% path length and execution time compared to the existing methods.

WomBot: an exploratory robot for monitoring wombat burrows

In this study we evaluate the design and efficacy of Wombot, an exploratory robot used to study environmental conditions within wombat burrows. Our purpose-built robot traverses through the difficult terrain present in wombat burrows whilst facilitating placement and retrieval of environmental data loggers. Our preliminary results suggest that the environmental conditions present within the burrows would result in a long mite survival time which shows significant risk for spreading infestations throughout a wombat population.Article HighlightsWombats live in difficult to observe burrows and suffer from mange cased by Sarcoptes scabiei.A teleoperated robot was designed to traverse the difficult terrain within burrows whilst placing and retrieving environmental loggers.Cool and humid environmental conditions within burrows suggest a relatively long mite survival time of 16–18 days

Artificial Moral Patients: Mentality, Intentionality, and Systematicity

In this paper, we defend three claims about what it will take for an AI system to be a basic moral patient to whom we can owe duties of non-maleficence not to harm her and duties of beneficence to benefit her: (1) Moral patients are mental patients; (2) Mental patients are true intentional systems; and (3) True intentional systems are systematically flexible. We suggest that we should be particularly alert to the possibility of such systematically flexible true intentional systems developing in the areas of exploratory robots and artificial personal assistants. Finally, we argue that in light of our failure to respect the well-being of existing biological moral patients and worries about our limited resources, there are compelling moral reasons to treat artificial moral patiency as something to be avoided at least for now.

Tactile design of manipulator fingers based on fingertip/textilefriction-induced vibration stimulations

Textile-like soft and flexible products are widely used in our daily life. Understanding the relationship between the tactilesensations of textiles and the tactile stimuli is essential for developing humanoid robot’s finger haptic system, especiallyfor certain kind of robot systems such as service robots and exploratory robots. This paper built a frequency space thatcan qualitatively represent a roughness sensation of textiles by a developing independently random match algorithm incombination with neurophysiological features of cutaneous mechanoreceptors. The experimental results show that thesum of amplitude in frequency range between 18 and 118 Hz can effectively describe the roughness sensory of textilewith accuracies of 98.5%. In other words, by applying the sum of amplitude in frequency range between 18 and 118 Hzcould successfully match roughness sensation of textiles, and it will help engineer of humanoid robot design manipulatorfinger haptic system in textile field.

Active Scene Understanding via Online Semantic Reconstruction

AbstractWe propose a novel approach to robot‐operated active understanding of unknown indoor scenes, based on online RGBD reconstruction with semantic segmentation. In our method, the exploratory robot scanning is both driven by and targeting at the recognition and segmentation of semantic objects from the scene. Our algorithm is built on top of a volumetric depth fusion framework and performs real‐time voxel‐based semantic labeling over the online reconstructed volume. The robot is guided by an online estimated discrete viewing score field (VSF) parameterized over the 3D space of 2D location and azimuth rotation. VSF stores for each grid the score of the corresponding view, which measures how much it reduces the uncertainty (entropy) of both geometric reconstruction and semantic labeling. Based on VSF, we select the next best views (NBV) as the target for each time step. We then jointly optimize the traverse path and camera trajectory between two adjacent NBVs, through maximizing the integral viewing score (information gain) along path and trajectory. Through extensive evaluation, we show that our method achieves efficient and accurate online scene parsing during exploratory scanning.

About Robotics, Mechatronics and Automation that Help us Conquer the Cosmic Space

Here we have to mention that all these SF writings and many others that have existed over time, especially in the 20th century, have influenced alongside obvious screenings, young people and not just them, to think more about our role, robots, into a better world. The robot's key role is to help the man make his work easier, safer, more enjoyable, just like a computerized machine that helps us work faster and better, the robot has an obvious role in making work easier, to work in our place when we are tired, when work is exhausting and repetitive, when the environment is toxic, hostile, dangerous and in many other situations. However, it is time to say that the role of the robot in the future is altogether another, namely, to help us conquer the cosmic space to expand ourselves as a race in the whole universe in which we are now. In fact, this is the robot's humanitarian role and in the future, it can be developed and prepared just for that purpose. Exploratory robots are robots that operate in hard-to-reach and dangerous locations, telegraph or partially autonomous. They can work for example in a region in military conflict, on the Moon or on Mars. A geared navigation on the ground in the last two cases is impossible due to distance. Communication signals arrive at their destination in a matter of hours and their reception lasts as long. In such situations, robots have to be programmed with several types of behavior, from which they choose the most appropriate and execute it. This type of robot equipped with sensors was also used to research pyramid wells. Several cryobots (cryo robots) have already been tested by NASA in Antarctica. This type of robot can reach up to 3,600 m through the ice. Cryobots can thus be used in polar head research on Mars and Europe in the hope of alien living. NASA has always said that understanding how to live and work in space for long periods of time has been a key goal of the International Space Station. But, from the White House, it may seem expensive this race around the Earth, considering that the mission costs about $8 million a day. Space makes us anxious. We are anxious that things go smoothly as if space flight should be infallible like a flight to London. And we are looking forward to a return on investment. We fly in space because of human ambition, because nothing gives us more resistance than trying to do what we have not done before. And we're flying in space because space is the eighth continent. We may eventually need asteroid or lunar resources, depending on how we manage the resources we have here on Earth. Eventually, we should become a species that will conquer other planets, whether we are no longer inside or that we actually destroy it or it will be destroyed.

About Robotics, Mechatronics and Automation that Help us Conquer the Cosmic Space

Here we have to mention that all these SF writings and many others that have existed over time, especially in the 20th century, have influenced alongside obvious screenings, young people and not just them, to think more about our role, robots, into a better world. The robot's key role is to help the man make his work easier, safer, more enjoyable, just like a computerized machine that helps us work faster and better, the robot has an obvious role in making work easier, to work in our place when we are tired, when work is exhausting and repetitive, when the environment is toxic, hostile, dangerous and in many other situations. However, it is time to say that the role of the robot in the future is altogether another, namely, to help us conquer the cosmic space to expand ourselves as a race in the whole universe in which we are now. In fact, this is the robot's humanitarian role and in the future, it can be developed and prepared just for that purpose. Exploratory robots are robots that operate in hard-to-reach and dangerous locations, telegraph or partially autonomous. They can work for example in a region in military conflict, on the Moon or on Mars. A geared navigation on the ground in the last two cases is impossible due to distance. Communication signals arrive at their destination in a matter of hours and their reception lasts as long. In such situations, robots have to be programmed with several types of behavior, from which they choose the most appropriate and execute it. This type of robot equipped with sensors was also used to research pyramid wells. Several cryobots (cryo robots) have already been tested by NASA in Antarctica. This type of robot can reach up to 3,600 m through the ice. Cryobots can thus be used in polar head research on Mars and Europe in the hope of alien living. NASA has always said that understanding how to live and work in space for long periods of time has been a key goal of the International Space Station. But, from the White House, it may seem expensive this race around the Earth, considering that the mission costs about $ 8 million a day. Space makes us anxious. We are anxious that things go smoothly as if space flight should be infallible like a flight to London. And we are looking forward to a return on investment. We fly in space because of human ambition, because nothing gives us more resistance than trying to do what we have not done before. And we're flying in space because space is the eighth continent. We may eventually need asteroid or lunar resources, depending on how we manage the resources we have here on Earth. Eventually, we should become a species that will conquer other planets, whether we are no longer inside or that we actually destroy it or it will be destroyed.

The synthesis of a segmented stair-climbing wheel

The article describes the process of development of an essentially new wheel suitable both for moving on flat ground and for travelling on stairs. The stair-climbing wheel is composed of rotary circular segments arranged around a shared carrier with arms to form a complete circular profile of the wheel adapted for moving on flat ground; for travelling on stairs, individual segments are rotated by an appropriate angle to touch down tangentially on the stepping surface of the stairs. The dimensions of individual segments, the centre of rotation of individual segments and the angle of their partial turn have been chosen so that the length of the arc along which the circular segment rolls is equal to the length of the stepping surface of an average stair, and, at the same time, the circular segment touches down tangentially on the stepping surface while the wheel turns around the edge of the previous segment. Using the rotation angle of the turnable segments, the wheel can be adapted to the height of non-standard stairs. The segments can be inclined in both directions for bidirectional movement of the wheel up and down the stairs. An undercarriage equipped with these wheels can be used in the field of exploratory robots and for the transportation of persons and materials on stairs.

Performance evaluation of underwater platforms in the context of space exploration

Robotic platforms are essential for future human planetary and lunar exploration as they can operate in more extreme environments with a greater endurance than human explorers. In this era of space exploration, a terrestrial analog that can be used for development of the coordination between manned and robotic vehicles will optimize the scientific return of future missions while concurrently minimizing the downtime of both human explorers and robotic platforms. This work presents the use of underwater exploratory robots – autonomous underwater vehicles (AUV), remotely operated vehicles (ROV), and manned submersibles – as analogues for mixed human–robot exploration of space. Subaqueous settings present diverse challenges for navigation, operation and recovery that require the development of an exploration model of a similar complexity as required for space exploration. To capitalize on the strengths of both robotic and human explorers this work presents lessons learnt with respect to the fields of human–robotic interface (HRI) and operator training. These are then used in the development of mission evaluation tools: (1) a task efficiency index (TEI), (2) performance metrics, and (3) exploration metrics. Although these independent evaluations were useful for specific missions, further refinement will be required to fully evaluate the strengths and capabilities of multiple platforms in a human–robotic exploration campaign in order to take advantage of unforeseen science opportunities in remote settings.

Four-Wheeled Hopping Robot with Attitude Control

Because a hopping robot moves long distances at minimum energy and can observe its surrounding from high points when it jumps, it is expected to explore microgravity environments effectively. Despite the importance of attitude control in such exploratory robots, few attitude control mechanisms have been proposed. This paper proposes a four-wheeled hopping robot that hops horizontally and lands without bouncing. Its wheels are applied to attitude control in the air. A simulation study and free-fall experiments verified the feasibility of the proposed mobility and the applicability of the robot.