Adaptive Latency Prediction and Haptic Feedback Optimization System for Mission-Critical Teleoperations in Haptic Internet Networks

Abstract

The invention is a system that dynamically analyzes the delay times between the operator and the robotic manipulator in mission-critical teleoperations performed over haptic internet connection, and optimizes haptic feedback signals according to these delays. The system includes the Operator Control Station (1), Haptic Feedback Module (2), Network Delay Analysis Unit (3), Adaptive Force Scaling Algorithm (4), Robotic Manipulator (5), and Real-Time Network Monitoring Sensor (6). The Adaptive Force Scaling Algorithm (4) ensures accurate operator perception by smoothing or strengthening the force feedback signals according to network delay data. By detecting instantaneous fluctuations in the network, the system minimizes the timing error of the force information transmitted to the operator and reduces safety risks.

Description

1 TARIFF ADAPTIVE FOR MISSION-CRITICAL TELEOPERATIONS IN TACTILE INTERNET NETWORKS DELAY PREDICTION AND HAPTIC FEEDBACK OPTIMIZATION SYSTEM Technical Area 5 The invention relates to robotic communication networks and haptic internet technologies. Specifically, the task... In critical teleoperation applications, the delay times between the operator and the robot. dynamically analyzes and optimizes haptic feedback signals based on these delays. It is a system that does. 10 State of the Art Current teleoperation systems transmit the operator's movements to the robotic system while maintaining a fixed position. It operates based on bandwidth and latency assumptions. However, the real-time network 15 Variations such as conditions, packet loss, and jitter affect the operator's haptic feedback. This leads to inconsistencies in the process. This is especially true with surgical robots or dangerous devices. Operator misperceptions in mission-critical systems such as ordnance disposal robots This leads to incorrect actions and maneuvers. In current systems, delay increases. haptic feedback signals are either completely interrupted or provide the operator with misleading force information. 20 These deficiencies are being communicated. These shortcomings disrupt system stability during teleoperation and This increases security risks. Purpose of the Invention The invention enables mission-critical teleoperations conducted via haptic internet connection, estimating network latency in real time and using haptic feedback based on that estimate. It aims to provide a system that regulates the operator's tactile perception. adaptively activates force feedback signals depending on the delay time to protect against damage. It aims at scaling. The main purpose of the invention is to detect instantaneous fluctuations in the network. 30 The aim is to minimize the timing error in the force information transmitted to the operator. In this way, the operator accurately determines the hardness or resistance of the surface the robotic arm contacts with precise timing. The system enables the user to sense haptic signals in high latency situations. by softening the operator's overreaction and preventing the system from becoming unstable It prevents packet loss in the haptic internet network. Furthermore, the invention provides artificial intelligence (35) when packet loss occurs. 2 By completing the missing data with a neural network-based prediction mechanism, a seamless process is achieved. It forms a control loop. Figures that will help understand the invention. Figure 1 shows a general representation of the system that is the subject of the invention. Explanation of Part References 1: Operator Control Station 10 2: Haptic Feedback Module 3: Network Latency Analysis Unit 4: Adaptive Force Scaling Algorithm 5: Robotic Manipulator 6: Real-Time Network Monitoring Sensor 15 Detailed Description of the Invention The invention enables mission-critical teleoperations via haptic internet connectivity. It is a system that performs the operator's physical movements to the robotic manipulator (5) 20 a structure that transmits and haptically reports the robot's environmental interactions back to the operator Operator Control Station (1) is the interface through which the operator controls the robot and this Commands received via the interface are transmitted over the network to the robotic manipulator (5). The Haptic Feedback Module (2) receives the force from the end effector of the robotic manipulator (5) and It is the mechanism that transmits touch data to the operator. This module is located in the operator's hand and contains 25 It simulates the sensation of contact by applying force to the controller. However, delays in the network can affect this. It can disrupt the timing of the sensation, causing the operator to make incorrect decisions. Network Delay Analysis Unit (3), operator control station (1) and robotic manipulator (5) It is a unit that continuously measures the round-trip times (RTT) of data packets between two countries. The unit works integrated with the real-time network monitoring sensor (6) to detect packet loss, jitter and 30 The Network Latency Analysis Unit (3) analyzes the latency times in milliseconds. It shares data with the Adaptive Force Scaling Algorithm (4). The Adaptive Force Scaling Algorithm (4) forms the unique technical core of the system. This algorithm is formed by the delay transmitted by the Network Delay Analysis Unit (3). It calculates a "Delay Risk Score" using the data. If the delay time exceeds the defined critical 35 If the threshold value exceeds (e.g., 10ms), the algorithm sends the haptic feedback module (2) 3 It sends a command to soften the force signals. This process prevents the operator from receiving sudden and harsh force feedback. By receiving notifications, it prevents him from making the wrong maneuver. The Robotic Manipulator (5) is the hardware that performs the task in the physical environment. In the end effector Thanks to the pressure and force sensors it contains, it can determine the hardness and resistance of the object it comes into contact with. It collects information. This data is used to monitor network conditions through a real-time network monitoring sensor (6). They are packaged together and sent to the operator. Real-Time Network Monitoring Sensor (6) detects packet delays and losses at the network layer. It is a software and hardware unit that detects bottlenecks. This sensor identifies bottlenecks in the network. It provides input for the Adaptive Force Scaling Algorithm (4). The system's operating scenario is as follows: Operator, Operator Control Station (1) 10 It moves the robotic manipulator (5) over it. The robotic manipulator (5) makes contact with an object. When it does, the contact force data is collected by the Real Time Network Monitoring Sensor (6) through the network. It is packaged with the conditions. The Network Latency Analysis Unit (3) measures the transmission time of these packets. and calculates the delay time. The Adaptive Force Scaling Algorithm (4) calculates The force modulates the feedback signal according to the delay time; for example, as the delay increases, it becomes 15. By reducing the amplitude of the force, it provides the operator with smoother feedback. Finally, The Haptic Feedback Module (2) transmits the optimized force signal to the operator, ensuring safety. and provides a stable teleoperation experience. 25 35

Claims

4 REQUESTS 1. In mission-critical teleoperations conducted via haptic internet connection, Dynamically analyzing the delay times between the operator and the robotic manipulator. and a system that optimizes haptic feedback signals according to these delays, 5 feature; - Operator Control Station (1), which is the interface through which the operator controls the robot. - Haptic Feedback, which transmits force data from the robotic manipulator to the operator. Module (2), - 10 data packets between operator control station (1) and robotic manipulator (5) Network Latency Analysis Unit (3), which measures round trip times, - smoothing force feedback signals based on network latency data or The Adaptive Force Scaling Algorithm (4) that strengthens - Robotic Manipulator (5) performing the task in the physical environment and - Real-Time Networking 15 detects packet delays and losses at the network layer. Monitoring Sensor (6) It includes. 25 35

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