Precise and efficient performance in remote robotic teleoperation relies on intuitive interaction. This requires both accurate control actions and complete perception (vision, haptic, and other sensory feedback) of the remote environment. Especially in immersive remote teleoperation, the complete perception of remote environments in 3D allows operators to gain improved situational awareness. Color and Depth (RGB-D) cameras capture remote environments as dense 3D point clouds for real-time visualization. However, providing enough situational awareness needs fast, high-quality data transmission from acquisition to virtual reality rendering. Unfortunately, dense point-cloud data can suffer from network delays and limits, impacting the teleoperator’s situational awareness. Understanding how the human eye works can help mitigate these challenges. This paper introduces a solution by implementing foveation, mimicking the human eye’s focus by smartly sampling and rendering dense point clouds for an intuitive remote teleoperation interface. This provides high resolution in the user’s central field, which gradually reduces toward the edges. However, this systematic visualization approach in the peripheral vision may benefit or risk losing information and burdening the user’s cognitive load. This work investigates these advantages and drawbacks through an experimental study and describes the overall system, with its software, hardware, and communication framework. This will show significant enhancements in both latency and throughput, surpassing 60% and 40% improvements in both aspects when compared with state-of-the-art research works. A user study reveals that the framework has minimal impact on the user’s visual quality of experience while helping to reduce the error rate significantly. Further, a 50% reduction in task execution time highlights the benefits of the proposed framework in immersive remote telerobotics applications.

Latency hinders a mobile robot teleoperator's ability to perform remote tasks. However, this effect is not well modeled. This paper develops a model for teleoperator steering behavior as a PD controller based on projected lateral displacement, which was tuned to reflect user performance determined by a 31-subject user study under constant and variable latency (having mean latencies between 0 and 750 ms). Additionally, we determined that operator performance under variable latency could be mapped to the expected performance of an equivalent constant latency. We then tested additional latency distributions in simulation and demonstrated equivalent steering performance among several different latency distributions.

This paper proposes a new algorithm, known as the Segmentation Algorithm, which provides model-based, real-time, whole-arm collision avoidance for telerobotic applications. The work presented here is an extension and modification of potential field theory. Novel aspects of the algorithm include the application of a hierarchical segmentation technique to minimize on-line processing and the development of procedures which account for workspace object translation, rotation, and grasping. The'SA outputs torques, which, when applied to the control arm, prevent the teleoperator from driving the remote arm into a collision. The teleoperator actually feels workspace objects that are spatially close to the remote arm—an experience known as virtual force-reflection. The SA's performance has been analyzed in terms of its speed and efficiency vis a vis various system parameters, including workspace object distribution, size, and number. Simulation results show that the SA succeeds in providing real-time collision avoidance where less elegant brute force algorithms fail.

This paper describes the robotics facilities and associated research program of the Jet Propulsion Laboratory, lead center in telerobotics for the United States National Aeronautics and Space Administration. Emphasis is placed on evolution from teleoperation to remote System automation. Research is described in manipulator modelling and control, real-time planning and monitoring, navigation in outdoor terrain, real-time sensing and perception, human-machine interface, and overall System architectures. Applications to NASA missions emphasize robotic spacecraft for solar System exploration, satellite servicing and retrieval, assembly of structures, and surveillance. Applications to military missions include battlefield navigation, surveillance, logistics, command and control.

Complex tasks that need to be performed through teleoperation led to the development of multifinger robot hands. A dextrous master is a multi-DOF controller which is worn by the operator in order to teleoperate these anthropomorphic hands. Force feedback is very useful when there is interaction with the environment. Providing force feedback to dextrous masters is an area of active research. We outline some of the human factors that influence the design of such masters. Of obvious importance is the hand geometry and the desired number of degrees of freedom. Additional criteria relate to the force perception of the hand. Finally, the man-machine impedance is of importance, since at the man/machine interface there are two impedances acting in series. One is the effective impedance of the human operator holding the master controller, the second is the impedance of the master controller being manipulated.

The control stategy for a dextrous masters is different from the general case of bilateral teleoperation since it models the human hand in much more detail. Such a model is discussed together with the selection of actuators used for force feedback control. Existing prototypes of dextrous masters with force feedback are then reviewed. These are the Servo Controlled Manipulator Device, the Portable Dextrous Force Feedback Master (P.D.M.F.F.), the Remote Handler, and the Advanced Multiple DOF Force Reflective Hand/Wrist Master.

Draper Small Autonomous Aerial Vehicle (DSAAV), MITy and SMART micro-rovers, Companion mini-rover, and Vorticity Control Unmanned Undersea Vehicle (VCUUV) are highlighted. DSAAV demonstrated autonomy with GPS/INS integration and vision processing. The micro- and mini-rovers investigated ground based autonomy with extensive mapping and planning integration. VCUUV is a flexible-hull UUV which propels and maneuvers like a tuna.

A six axis robot has been connected to the World Wide Web at http://telerobot.mech.uwa.edu.au/. The robot was made available on the World Wide Web in September 1994 and has been through many revisions since that time. The remote user receives static images of the robot's work space and can manipulate wooden blocks.

The implementation and application of this interface to telerobotics is discussed. Useability and operator behaviour are investigated through analysis of movement records. Questions addressed are: What is the level of interest in this technique and is it a practical interface for telerobotics.

The paper deals with the modelling of unknown objects and location determination of known ones. The operator models objects using data issued from the video image and a time of flight infra red range finder. We present methods to build an embodying volume for unknown objects. These methods are available for polyhedral and conical objects, which represent the basis of most industrial environments. The location determination of known objects is determined using 2D clues obtained through video image. A two-step algorithm is implemented and assessed. The first step is available in case of object large motion, it is a geometric algorithm, which doesn't use redundant data; it provides a first estimate of the pose. The second step is available in case of object small motion. A linear approach is carried out to determine the pose. It allows the use of redundant data, so it improves the accuracy achieved after the first step.