Safe and Secure Autonomous Systems

Compliance actuation systems are efficient and safe, drawing attention to their development. However, compliance has caused bandwidth loss, instability, and mechanical vibration in robotic systems. Variable physical damping was introduced to address these issues. This paper presents a technique for obtaining variable damping properties using an electromagnetic brake. The relationship mapping of the voltage and the braking torque is studied and applied to the variable damping concept. A new model is proposed to demonstrate the actuation system performance gained by introducing physical damping. The experimental setup comprises an electromagnetic brake and a motor with an integrated controller for speed control and torque feedback. The motor provides the motion, while the electromagnetic brake replicates the damping through a friction mechanism. The variable damping concept was evaluated experimentally using a 1-degree-of-freedom rotational system. Experimental results show that the proposed concept can generate the desired mechanical damping with a high degree of fidelity. Full article

This paper proposes a robust algorithm based on a fixed-time sliding mode controller (FTSMC) for a Quadrotor aircraft. This approach is based on Lyapunov theory, which guarantees system stability. Nonlinear error dynamics techniques are used to achieve accurate trajectory tracking in the presence of disturbances. The performance of the FTSMC is compared with the typical non-singular terminal sliding mode controller (NTSMC) to evaluate its effectiveness. The numerical results show that FTSMC is more efficient than the typical NTSMC in disturbance reduction. Full article

Steam mopping is an eco-friendly solution for cleaning and disinfecting floors, avoiding harsh chemicals or harmful UV lights. Currently, commercial steam mopping systems are manually operated, which is laborious and unsafe. This work presents the design methodology of a novel, eco-friendly autonomous steam mopping robot named ‘Snail’ for cleaning and disinfecting typical indoor floors, namely tile, carpet, concrete, vinyl, sealed wood, and rugs. Our work is mainly focused on (1) the mechanical system design, including the locomotion, steam dispenser, and mopping unit, (2) the hardware and software architecture, and (3) the motion control system’s design for smooth maneuverability and mitigating friction forces. A high-gain friction estimator is proposed, whose output is exploited by the motion controller to follow the desired path and compensate for the traction-based locomotion disturbances due to extensive mop contact with a rough-textured floor, such as carpet. The proposed autonomous steam mopping robot’s efficiency is validated with different floors with zig-zagging cleaning patterns, setting a minimum of 100 °C as the disinfecting steam criterion. Using the proposed motion control algorithm, we validate the smooth maneuverability, assuring the robot traverses with a given speed and follows the trajectory even on a rough carpeted floor. The cleaning efficiency is tested by removing hard stains, consuming less water, and faster wet floor drying. The robot used only one liter of water to clean a 5 ${\mathrm{m}}^2$ floor area, and the drying time was found to be four times faster than normal water mopping. The proposed steam mopping robot design is ideal for cleaning and disinfecting hospitals and eldercare centers, where hygiene is crucial, and promoting going green, avoiding harsh chemicals, and mitigating current cleaner labor concerns, including the risk of infection. Full article

Radio Frequency Identification (RFID) technology is a critical part of many Internet of Things (IoT) systems, including Medical IoT (MIoT) for instance. On the other hand, the IoT devices’ numerous limitations (such as memory space, computing capability, and battery capacity) make it difficult to implement cost- and energy-efficient security solutions. As a result, several researchers attempted to address this problem, and several RFID-based security mechanisms for the MIoT and other constrained environments were proposed. In this vein, Wang et al. and Shariq et al. recently proposed CRUSAP and ESRAS ultra-lightweight authentication schemes. They demonstrated, both formally and informally, that their schemes meet the required security properties for RFID systems. In their proposed protocols, they have used a very lightweight operation called $Cro(·)$ and $Rank(·)$, respectively. However, in this paper, we show that those functions are not secure enough to provide the desired security. We show that $Cro(·)$ is linear and reversible, and it is easy to obtain the secret values used in its calculation. Then, by exploiting the vulnerability of the $Cro(·)$ function, we demonstrated that CRUSAP is vulnerable to secret disclosure attacks. The proposed attack has a success probability of "1" and is as simple as a CRUSAP protocol run. Other security attacks are obviously possible by obtaining the secret values of the tag and reader. In addition, we present a de-synchronization attack on the CRUSAP protocol. Furthermore, we provide a thorough examination of ESRAS and its $Rank(·)$ function. We first present a de-synchronization attack that works for any desired $Rank(·)$ function, including Shariq et al.’s proposed $Rank(·)$ function. We also show that $Rank(·)$ does not provide the desired confusion and diffusion that is claimed by the designers. Finally, we conduct a secret disclosure attack against ESRAS. Full article

Recently, Zerrouki et al. proposed a Physically Unclonable Function (PUF) mutual authentication and session key establishment protocol for IoT (Internet of Things) devices. Zerrouki et al.’s PUF protocol is interesting because it does not require the storage of any sensitive information on the local memory of the IoT device, which avoids many potential attacks, especially side-channel attacks. Therefore, we carefully investigate the security of Zerrouki et al.’s PUF protocol under the leakage assumption of the session key. Our findings are in the following. First, Zerrouki et al.’s PUF protocol fails to provide known-key security. That is, the adversary can impersonate not only the server to cheat the IoT device but also the IoT device to cheat the server when the adversary corrupts a session key between the server and the IoT device. Second, Zerrouki et al.’s PUF protocol suffers from the key-compromise impersonation attack. It means that the adversary can impersonate the IoT device to cheat the server if the adversary discloses the server’s secret key. Third, Zerrouki et al.’s PUF protocol does not support backward secrecy for the session key. That is, the adversary is always able to derive the session key from the previous session key. We also suggest the root cause of these security flaws in Zerrouki et al.’s PUF protocol. As a case study, our cryptanalysis results would promote a security model for more robust and efficient PUF authentication and session key establishment protocol. Moreover, our idea of the key compromise can be used to evaluate other novel PUF protocol designs. Full article

Issues of aviation flight safety conducted with an on-board information exchange system are discussed. The system information analysis method is used. An analysis of in-flight hazard sources and the means of their elimination from the information exchange point of view are carried out including the influence of the information exchange system’s parameters, work algorithm and architecture. The value of information exchange speed on safety in dynamic flight conditions is discussed. A modification of architecture and the information exchange system algorithm are proposed to increase the exchange speed and the whole system’s effectiveness based on parallel processing as well as to enhance the probability of successful elimination of an emergency situation. Full article

In this study, a novel end-to-end path planning algorithm based on deep reinforcement learning is proposed for aerial robots deployed in dense environments. The learning agent finds an obstacle-free way around the provided rough, global path by only depending on the observations from a forward-facing depth camera. A novel deep reinforcement learning framework is proposed to train the end-to-end policy with the capability of safely avoiding obstacles. The Webots open-source robot simulator is utilized for training the policy, introducing highly randomized environmental configurations for better generalization. The training is performed without dynamics calculations through randomized position updates to minimize the amount of data processed. The trained policy is first comprehensively evaluated in simulations involving physical dynamics and software-in-the-loop flight control. The proposed method is proven to have a 38% and 50% higher success rate compared to both deep reinforcement learning-based and artificial potential field-based baselines, respectively. The generalization capability of the method is verified in simulation-to-real transfer without further training. Real-time experiments are conducted with several trials in two different scenarios, showing a 50% higher success rate of the proposed method compared to the deep reinforcement learning-based baseline. Full article