Semi-autonomous serially connected multi-crawler robot for search and rescue

Equilibrium Conformation of a Novel Cable-Driven Snake-Arm Robot under External Loads

Based on the anti-parallelogram mechanism, an approximate cylindrical rolling joint is proposed to develop a novel cable-driven snake-arm robot with multiple degrees of freedom (DOF). Furthermore, the kinematics of the cable-driven snake-arm robot are established, and the mapping between actuator space and joint space is simplified by bending decoupling motion in the multiple segments. The workspace and bending configurations of the robot are obtained. The static model is established by the principle of minimum potential energy. Furthermore, the simplified cable constraints in the static model are proposed through Taylor expansion, which facilitates the equilibrium conformation analysis of the robot under different external forces. The cable-driven snake-arm robot prototype is developed to verify the feasibility of the robot design and the availability of the static model through the experiments of the free bending motion and the external load on the robot.

LPWAN-Based Real-Time 2D SLAM and Object Localization for Teleoperation Robot Control

In this study, the teleoperation robot control on a mobile robot with 2D SLAM and object localization using LPWAN is proposed. The mobile robot is a technology gaining popularity due to flexibility and robustness in a variety of terrains. In search and rescue activities, the mobile robots can be used to perform some missions, assist and preserve human life. However, teleoperation control becomes a challenging problem for this implementation. The robust wireless communication not only allows the operator to stay away from dangerous area, but also increases the mobility of the mobile robot itself. Most of teleoperation mobile robots use Wi-Fi having high-bandwidth, yet short communication range. LoRa as LPWAN, on the other hand, has much longer range but low-bandwidth communication speed. Therefore, the combination of them complements each other’s weaknesses. The use of a two-LoRa configuration also enhances the teleoperation capabilities. All information from the mobile robot can be sent to the PC controller in relatively fast enough for real-time SLAM implementation. Furthermore, the mobile robot is also capable of real-time object detection, localization, and transmitting images. Another problem of LoRa communication is a timeout. We apply timeout recovery algorithms to handle this issue, resulting in more stable data. All data have been confirmed by real-time trials and the proposed method can approach the Wi-Fi performance with a low waiting time or delay.

AiRobSim: Simulating a Multisensor Aerial Robot for Urban Search and Rescue Operation and Training

Unmanned aerial vehicles (UAVs), equipped with a variety of sensors, are being used to provide actionable information to augment first responders' situational awareness in disaster areas for urban search and rescue (SaR) operations. However, existing aerial robots are unable to sense the occluded spaces in collapsed structures, and voids buried in disaster rubble that may contain victims. In this study, we developed a framework, AiRobSim, to simulate an aerial robot to acquire both aboveground and underground information for post-disaster SaR. The integration of UAV, ground-penetrating radar (GPR), and other sensors, such as global navigation satellite system (GNSS), inertial measurement unit (IMU), and cameras, enables the aerial robot to provide a holistic view of the complex urban disaster areas. The robot-collected data can help locate critical spaces under the rubble to save trapped victims. The simulation framework can serve as a virtual training platform for novice users to control and operate the robot before actual deployment. Data streams provided by the platform, which include maneuver commands, robot states and environmental information, have potential to facilitate the understanding of the decision-making process in urban SaR and the training of future intelligent SaR robots.

TAOYAKA-III: A Six-Legged Robot Capable of Climbing Various Columnar Objects

Inspection and maintenance of large industrial plants are important tasks expected of robots. Furthermore, it is expected that an autonomous robot will be able to climb various arbitrary columnar objects, such as pipes, pillars, and trees. These tasks would be very difficult for conventional robots, because most must first assess the shape of the object and control many bodily degrees of freedom in order to climb. In our previous work, we developed a flexible manipulator, inspired by an octopus, which could grasp various objects without sensors or controls. Its flexible body passively adapted to differences in the objects’ features. In this research, we apply that mechanism to a six-legged climbing robot, which can climb arbitrary columnar objects without first sensing their shapes.

Design and Realize a Snake-Like Robot in Complex Environment

Aiming at high performance requirements of snake-like robots under complex environment, we present a control system of our proposed design which utilizes a STM32 as the core processor and incorporates real-time image acquisition, multisensor fusion, and wireless communication technology. We use Solidworks to optimize the design of head, body, and tail joint structure of the snake-like robot. The system is a real-time system with a simple-circuit structure and multidegrees of freedom are attributed to the flawless design of control system and mechanical structure. We propose a control method based on our simplified CPG model. Meanwhile, we improve Serpenoid control function and then investigate how different parameters affect the motion gait in terms of ADAMS emulation. Finally, experimental results show that the snake-like robot can tackle challenging problems including multi-information acquisition and processing, multigait stability, and autonomous motion and further verify the reliability and accuracy of the system in our combinatory experiments.

Semi-Autonomous Multi-Legged Robot with Suckers to Climb a Wall

In recent years, the maintenance and inspection of old buildings have become important tasks for robots. Such robots are also expected to be used for search and rescue missions in the case of disasters. In our previous work, we developed a multi-legged robot for such tasks. In the current work, we focused on the task of climbing a vertical wall. We improved our previous robot and developed a flexible leg with a sucker to climb a wall.

Robust Neuro-Optimal Control of Underactuated Snake Robots With Experience Replay

In this paper, the problem of path following for underactuated snake robots is investigated by using approximate dynamic programming and neural networks (NNs). The lateral undulatory gait of a snake robot is stabilized in a virtual holonomic constraint manifold through a partial feedback linearizing control law. Based on a dynamic compensator and Line-of-Sight guidance law, the path-following problem is transformed to a regulation problem of a nonlinear system with uncertainties. Subsequently, it is solved by an infinite horizon optimal control scheme using a single critic NN. A novel fluctuating learning algorithm is derived to approximate the associated cost function online and relax the initial stabilizing control requirement. The approximate optimal control input is derived by solving a modified Hamilton-Jacobi-Bellman equation. The conventional persistence of excitation condition is relaxed by using experience replay technique. The proposed control scheme ensures that all states of the snake robot are uniformly ultimate bounded which is analyzed by using the Lyapunov approach, and the tracking error asymptotically converges to a residual set. Simulation results are presented to verify the effectiveness of the proposed method.