Keywords: Path Planning, Local and Global Roadmap Planning, Advanced Driver Assistance Systems
Abstract: The acceptability by a population for new technology is conditioned by its benefits and its adaptability. While an autonomous vehicle could be a nice solution as an intelligent transportation system to decrease road crashes, traffic jams, etc., the choice of a driving style (relaxed/sporty) could be a good factor of adaptability. This study presents a method to optimize a local overtaking trajectory defined as a sigmoid function integrating constraints of comfort, safety, and path continuity. An only one driving style parameter allows obtaining different paths from smooth to tight shapes respecting previous constraints. Simulations of use cases show good performance of the developed algorithm.

Keywords: Task and Motion Planning, Path Planning
Abstract: A widespread trigger of discomfort in road vehicles is motion sickness (MS), which describes the motion induced occurrence of symptoms such as dizziness, nausea and vomiting. This paper presents an approach to consider MS in optimal trajectory planning for autonomous passenger vehicles. Optimization based planning is a well suited method as it explicitly considers hard constraints, e.g. road bounds, and ensures that the vehicle is able to follow the planned trajectory even at the limits of handling. However, solving the optimization problem numerically can be expensive especially with high order models. Complex models may even lead to poor convergence properties of the numerical algorithms. In this work, we propose a model incorporating passive head tilting and the subjective vertical conflict (SVC) model. We show that when assuming comfortable driving, significant simplifications can be done by approximating the vertical conflict as jerk. We embed the SVC model in the planning problem, and show that similar results are achieved when considering either vertical conflict or jerk. In any case, MS can be predictively suppressed even on roads that prone to trigger motion sickness.

Keywords: Robot Navigation, Programming and Vision, Obstacle Detection and Avoidance, Path Planning
Abstract: This work proposes a complete autonomous navigation system for a tracked vehicle. The system enables a complete autonomous execution of waypoint and patrolling tasks selected by the user. It also enables user-vehicle shared autonomy, switching between the user teleoperation and the vehicle autonomous operation. Our navigation system uses the model predictive control scheme based on a navigation function. We propose the navigation function which takes into account changing environments, any-shape footprint, and non-holonomic motion of the tracked vehicle. Besides the waypoint and patrolling tasks, we implemented a fail-safe scenario in case of the user-vehicle communication loss, in which the vehicle returns autonomously to the previously visited goal where the communication was stable. The efficiency of the proposed system is validated by experimental results on the Komodo tracked vehicle.

Keywords: Task and Motion Planning, Localization and SLAM, Path Planning
Abstract: Autonomous robotic exploration has long attracted the attention of the robotics community and is a topic of high relevance. Deploying such systems in the real world, however, is still far from being a reality. In part, it can be attributed to the fact that most research is directed towards improving existing algorithms and testing novel formulations in simulation environments rather than addressing practical issues of real-world scenarios. This is the case of the fundamental problem of autonomously deciding when exploration has to be terminated or changed (stopping criteria), which has not received any attention recently. In this paper, we discuss the importance of using appropriate stopping criteria and analyse the behaviour of a novel criterion based on the evolution of optimality criteria in active graph-SLAM.

Keywords: Maneuverability, Path Planning, Trajectory Tracking
Abstract: The paper proposes a nonlinear control method for performing a backflip maneuver with a nano quadcopter. To perform the maneuver, first a feasible reference trajectory is designed that describes the intended state evolution. Then, the designed trajectory is precisely tracked by a nonlinear geometric controller that is able to track even highly challenging reference trajectories. The performance of the proposed method is evaluated and compared to a simple adaptive feedforward control strategy based on simulations and real-world experiments using Bitcraze Crazyflie nano quadcopters.

Keywords: Multi-Vehicle Systems, Driver Support Systems, Trajectory Tracking
Abstract: The forerunner UAV means a camera equipped drone flying in front of the advancing first responder units to increase driver situational awareness with an aerial view of the traffic situation and notification about imminent dangers. This article presents the software-in-the-loop (SIL) simulation of the concept including UNREAL4-Carla as the virtual reality environment with a firetruck driven through a game controller, the Matlab simulation of the DJI M600 forerunner hexacopter with UDP communication between firetruck and M600 and the real-time AI processing of synthetic images to detect ground vehicles and pedestrians. The target of SIL development is threefold. First, to test M600 autopilot and AI-based object detection in close to realistic conditions before the real flights. Second, to make an exhaustive feasibility study of the whole forerunner concept with several simulated situations. Third, to generate the required large amount of image data for AI object detection tuning. After introducing all parts of the SIL simulation the article presents an illustrative example evaluating the tracking of the ground vehicle with the M600 and the inference system results.

Keywords: Trajectory Tracking, Path Following, Maneuverability
Abstract: In the presented work, a trajectory is designed allowing an Unmanned Aerial Vehicle (UAV) to perform landing on a mobile platform. The proposed trajectory behaves in such a way that grants a seamless integration of information about the target landing platform into its design. This allows any generic tracking controller to follow the trajectory regardless of the target's dynamics or movement, as they are indirectly applied to the trajectory's architecture. The focus of this work is for fixed-wing aircraft to land on water surface vehicles but can be adjusted for different scenarios. One of which is used for the experimental corroboration of the proposed strategy in a real-world environment.

Keywords: Multi-Vehicle Systems, Control Systems and Technology, Estimation Algorithms and Theory
Abstract: Multi-vehicle aerial robots present great potential in accomplishing manipulation tasks, because of their high payload capacity and full manipulability in 3-dimensional space. Belonging to this class of aerial robots, the Flying Parallel Robot (FPR) is an architecture where a moving platform is supported collectively by a team of quadrotors with passive kinematic chains. While the modelling and control of the FPR in free space has been studied in the previous work, there is lack of consideration in robot-environment interaction, which is however significant to develop the industrial applications of such robots. In this paper, we implement an external wrench estimator and an impedance-based controller with force tracking capability to achieve the disturbance rejection and the physical interaction with the environment. Extensive experimental validations have shown the FPR capable of hovering in presence of additional payload and strong wind perturbations, and performing contact-based interaction tasks.