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Our human-robot collaboration research aims to improve the fluency and efficiency of interactions between humans and robots when executing a set of tasks in a shared workspace. During human-robot collaboration, a robot and a user must often complete a disjoint set of tasks that use an overlapping set of objects, without using the same object simultaneously. A key challenge is deciding what task the...
The efficiency of autonomous robots depends on how well they understand their operating environment. While most of the traditional environment models focus on the spatial representation, long-term mobile robot operation in human populated environments requires that the robots have a basic model of human behaviour.
In highly dynamic tasks that involve moving targets, planning is necessary to figure out when, where and how to intercept the target. In robotic table tennis in particular, motion planning can be very challenging due to time constraints, dimension of the search space and modelling uncertainties. To simplify the problem, conventional planning algorithms often rely on a fixed virtual hitting plane to...
In this paper, we discussed the simultaneous intervention problem that arises from human-robot teams. The problem concerns with the case that one human operator has to intervene with several robots at almost the same time and it cannot be handled properly by existing methods. A model predictive control(MPC) based mixed initiative controller was proposed to solve this problem by embedding an intention...
The paper presents an analysis of human-like reaching movements in manipulation of parallel flexible objects. To predict the trajectory of human hand, a minimum hand jerk model, based on the minimization of integral of squared hand jerk over the movement duration is established. It is shown that within this model the optimal hand trajectory is composed of a fifth order polynomial and two trigonometric...
Modeling of physical human-robot collaborations is generally a challenging problem due to the unpredictive nature of human behavior. To address this issue, we present a data-efficient reinforcement learning framework which enables a robot to learn how to collaborate with a human partner. The robot learns the task from its own sensorimotor experiences in an unsupervised manner.
This paper reports on a data-driven motion planning approach for interaction-aware, socially-compliant robot navigation among human agents. Autonomous mobile robots navigating in workspaces shared with human agents require motion planning techniques providing seamless integration and smooth navigation in such. Smooth integration in mixed scenarios calls for two abilities of the robot: predicting actions...
Human motion is fast and hard to predict. To implement a provably safe collision-avoidance strategy for robots in collaborative spaces with humans, an overapproximative prediction of the occupancy of the human is required, which needs to be calculated faster than real time. We present a method for computing volumes containing the entire possible future occupancy of the human, given its state, faster...
Aiming at the trajectory prediction in forecast handover process of early warning detection system, a method of prediction trajectory for unpowered gliding hypersonic vehicle in the gliding phase is proposed. Firstly, the motion characteristic of the unpowered glide hypersonic vehicle in gliding phase is analyzed to verify the feasibility of using a polynomial model to predict the target trajectory...
Aiming at the problem of trajectory prediction in air traffic control automation system, a new method of trajectory prediction based on aircraft motion model and grey theory is proposed. This method combines the aircraft motion model and the prediction method of grey theory, which realizes the real-time online trajectory prediction and improves the prediction accuracy. This prediction method has strong...
This paper proposed for comparison of two methods used to predict the trajectory of a moving object in 3D fields using Kalman Filter and Levenberg-Marquardt Least Squares. The Kalman Filter needs dynamic model of the object to predict trajectory, different from The Levenberg-Marquardt method requires previous movements of the object, and the system can determine the next move, to perform this experiment...
A novel scheme to solve the trajectory planning problem for quadrotors with model and state constraints is proposed. First the RRT (Rapidly-exploring Random Tree) algorithm is employed to generate an initial route in context of a 3D environment. Then with the model of quadrotoer, the MPC (Model Predictive Control) method is used to construct an inner simulator which can generate the trajectories satisfying...
We present the simulation of the application of the Model-based Predictive Control (MPC) of the drum level in a Combined Cycle Plant in order to minimize the time for reaching the highest capacity of plant, around 225 MW. In contrast to others control techniques, our simulation yields that the MPC has shown capabilities as to reach its expected power in about 40 minutes before than PID, time which...
Trajectory predictors are core components of many air traffic applications. This includes cockpit, dispatch, flight planning, strategic fleet planning, air traffic control, traffic flow management, and aviation research applications. In all these different approaches, aircraft performance models are often required such as, for instance, drag polar aerodynamic data and maximum thrust propulsion data...
Managing trajectory separation of unmanned aircraft is critical to ensuring accessibility, efficiency, and safety in low altitude airspace. The concept of a geo-fence has emerged as a way to manage trajectory separation. A geo-fence consists of distance buffers that enclose individual trajectories to identify a ‘keep-in’ region and/or enclose areas that identify ‘keep-out’ regions. The ‘keep-in’ geo-fence...
Major commercial (AAA) games increasingly transit to a semi-persistent or persistent format in order to extend the value of the game to the player, and to add new sources of revenue beyond basic retail sales. Given this shift in the design of AAA titles, game analytics needs to address new types of problems, notably the problem of forecasting future player behavior. This is because player retention...
We present an active learning architecture that allows a robot to actively learn which data collection strategy is most efficient for acquiring motor skills to achieve multiple outcomes, and generalise over its experience to achieve new outcomes for cumulative learning. In the present work, we consider the learning of tasks that are hierarchically organised, interrelated and more and more difficult...
This paper proposes a co-worker in-time Parts/tools Delivery to You robot, PaDY, in an automobile assembly line. Since co-worker robots share a workspace, the workers are at risk of colliding with them. Therefore, the safety of the workers has to be considered when operating such robots. In previous studies, the robot generally stops to ensure the worker's safety when a collision is detected, delaying...
Yangtze River is the world's busiest inland waterway. Ships need to be guided when passing through controlled waterways based on their trajectory predictions. Inaccurate predicted trajectories lead to non-optimal traffic signalling which may cause significant traffic jam. For the existing intelligent traffic signalling systems (ITSSs), ships are supposed to travel exactly along the mid-line of the...
This work proposes the use of Laguerre function in Predictive Functional Control (PFC) to produce well-posed decision making. The constant control input assumption of a classical PFC is replaced with the Laguerre polynomial and the steady state input of a system. With this slight modification, better consistency between model predictions and an actual system behaviour is achieved. In addition, the...
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