Literature points to persistent issues in human-automation interaction, which are caused either when the human does not understand the automation or when the automation does not understand the human. Design guidelines for human-automation interaction aim to avoid such issues and commonly agree that the human should have continuous interaction and communication with the automation system and its authority level and should retain final authority. This paper argues that haptic shared control is a promising approach to meet the commonly voiced design guidelines for human-automation interaction, especially for automotive applications. The goal of the paper is to provide evidence for this statement, by discussing several realizations of haptic shared control found in literature. We show that literature provides ample experimental evidence that haptic shared control can lead to short-term performance benefits (e.g., faster and more accurate vehicle control; lower levels of control effort; reduced demand for visual attention). We conclude that although the continuous intuitive physical interaction inherent in haptic shared control is expected to reduce long-term issues with human-automation interaction, little experimental evidence for this is provided. Therefore, future research on haptic shared control should focus more on issues related to long-term use such as trust, overreliance, dependency on the system, and retention of skills.

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Haptic shared control: smoothly shifting control authority?

Robustness and flexibility constitute the main advantages of multiple-robot systems with respect to single-robot ones as per the recent literature. The use of multiple unmanned aerial vehicles (UAVs) combines these benefits with the agility and pervasiveness of aerial platforms [1], [2]. The degree of autonomy of the multi-UAV system should be tuned according to the specificities of the situation under consideration. For regular missions, fully autonomous UAV systems are often appropriate, but, in general, the use of semiautonomous groups of UAVs, supervised or partially controlled by one or more human operators, is the only viable solution to deal with the complexity and unpredictability of real-world scenarios as in, e.g., the case of search and rescue missions or exploration of large/cluttered environments [3]. In addition, the human presence is also mandatory for taking the responsibility of critical decisions in high-risk situations [4].

Shared Control : Balancing Autonomy and Human Assistance with a Group of Quadrotor UAVs

In this paper, a novel decentralized control strategy for bilaterally teleoperating heterogeneous groups of mobile robots from different domains (aerial, ground, marine, and underwater) is proposed. By using a decentralized control architecture, the group of robots, which is treated as the slave side, is made able to navigate in a cluttered environment while avoiding obstacles, interrobot collisions, and following the human motion commands. Simultaneously, the human operator acting on the master side is provided with a suitable force feedback informative of the group response and of the interaction with the surrounding environment. Using passivity-based techniques, we allow the behavior of the group to be as flexible as possible with arbitrary split and join events (e.g., due to interrobot visibility/packet losses or specific task requirements) while guaranteeing the stability of the system. We provide a rigorous analysis of the system stability and steady-state characteristics and validate performance through human/hardware-in-the-loop simulations by considering a heterogeneous fleet of unmanned aerial vehicles (UAVs) and unmanned ground vehicles as a case study. Finally, we also provide an experimental validation with four quadrotor UAVs.

Bilateral Teleoperation of Groups of Mobile Robots With Time-Varying Topology

The feedback upon which operators in teleoperation tasks base their control actions differs substantially from the feedback to the driver of a vehicle. On the one hand, there is often a lack of sensory information; on the other hand, there is additional status information presented via the visual channel. Haptic feedback could be used to unload the visual channel and to compensate for the lack of feedback in other modalities. For collision avoidance, haptic feedback could provide repulsive forces via the control inceptor. Haptic feedback allows operators to interpret the repulsive forces as impedance to their control deflections when a potential for collision exists. Haptic information can be generated from an artificial force field (AFF) that maps environment constraints to repulsive forces. This paper describes the design and theoretical evaluation of a novel AFF, i.e., the parametric risk field, for teleoperation of an uninhabited aerial vehicle (UAV). The field allows adjustments of the size, shape, and force gradient by means of parameter settings, which determine the sensitivity of the field. Computer simulations were conducted to evaluate the effectiveness of the field for collision avoidance for various parameter settings. Results indicate that the novel AFF more effectively performs the collision avoidance function than potential fields known from literature. Because of its smaller size, the field yields lower repulsive forces, results in less force cancellation effects, and allows for larger UAV velocities. This indicates less operator control demand and more effective UAV operations, both expected to lead to lower operator workload, while, at the same time, increasing safety.

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Artificial Force Field for Haptic Feedback in UAV Teleoperation

In this paper we address the problem of controlling the motion of a group of unmanned aerial vehicles (UAVs) bound to keep a formation defined in terms of only relative angles (i.e. a bearing formation). This problem can naturally arise within the context of several multi-robot applications such as, e.g. exploration, coverage, and surveillance. First, we introduce and thoroughly analyze the concept and properties of bearing formations, and provide a class of minimally linear sets of bearings sufficient to uniquely define such formations. We then propose a bearing-only formation controller requiring only bearing measurements, converging almost globally, and maintaining bounded inter-agent distances despite the lack of direct metric information.The controller still leaves the possibility of imposing group motions tangent to the current bearing formation. These can be either autonomously chosen by the robots because of any additional task (e.g. exploration), or exploited by an assisting human co-operator. Fo...

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Modeling and Control of UAV Bearing Formations with Bilateral High-level Steering

This paper introduces four new collision avoidance systems for a remotely-operated helicopter using haptic feedback on the control stick of the operator. To calculate the feedback force artificial risk fields are used, which give an indication about the risk of hitting an obstacle. For each obstacle in the risk field a risk value is calculated, which is transformed to a risk vector, acting as an artificial force on the vehicle. All risk vectors are integrated into one avoidance vector, which is proportional to the feedback force to the operator. A basic risk field and a parameterized risk field are tested in simulations, together with two risk vector calculation methods, resulting in radial and normal risk vectors. The simulations show most promising results for the parameterized risk field with radial risk vectors and worst results for the basic risk field with normal vectors

Collision avoidance for a remotely-operated helicopter using haptic feedback

Due to the limited field of view of a camera, visual information may not be sufficient to control an unmanned aerial vehicle (UAV). In particular when the camera is not pointing into the direction of motion, perception of environment constraints can be considerably difficult. The use of haptic feedback would provide tactile cues complementing the information from the visual channel. This paper presents the results of an experimental evaluation of using haptic feedback for manual control of an UAV helicopter in a trajectory following task. The experiment involves controlling an UAV helicopter along a reference trajectory as fast and accurately as possible. The trajectory is represented by a three-dimensional tunnel-in-the-sky display of which the walls represent the environment constraints. The experiment only considers the horizontal plane. The results of the experiment indicate that haptic feedback can be used to support the operator in perceiving tunnel walls as environment constraints. The performance, control activity and workload strongly depend on the manner in which repulsive forces are fed back to the human operator.

H.W. Boschloo

Papers

Artificial Force Field for Haptic Feedback in UAV Teleoperation

Collision avoidance for a remotely-operated helicopter using haptic feedback

Effect of haptic feedback in a trajectory following task with an unmanned aerial vehicle