Demo: FoReCo – a forecast-based recovery mechanism for real-time remote control of robotic manipulators Milan Groshev Universidad Carlos III de Madrid Spain Javier Sacido Telcaria Ideas S.L. Spain Jorge Martín-Pérez Universidad Carlos III de Madrid Spain ABSTRACT This demonstration presents FoReCo [4], a solution to recover lost control commands in remotely controlled robots. In the demon- stration, visitors use a joystick to remotely control a robotic arm under the presence of packet losses in the wireless medium. The lost control commands result in a distorted trajectory of the robotic arm, thus, we deploy FoReCo to recover lost control commands using an ML model that we train with a real-world dataset. The demonstration shows how FoReCo recovers the lost commands, and how the robot arm operates smoothly despite the losses that are present in the wireless medium. CCS CONCEPTS • Networks →Cyber-physical networks. ACM Reference Format: Milan Groshev, Javier Sacido, and Jorge Martín-Pérez. 2022. Demo: FoReCo – a forecast-based recovery mechanism for real-time remote control of robotic manipulators. In ACM SIGCOMM 2022 Conference (SIGCOMM ’22 Demos and Posters), August 22–26, 2022, Amsterdam, Netherlands. ACM, New York, NY, USA, 3 pages. https://doi.org/10.1145/3546037.3546047 1 INTRODUCTION Real-time remote control of robotic manipulators is of high interest for industry 4.0 use cases [2], since it reduces costs and the exposure of operators to hazard situations. However, the presence of packet losses in the the network lead to trajectory deviations that prevent the robot from achieving the expected 99.9999% reliability [1]. The mechatronics and robotic community propose to overcome the lost/delayed control commands using time domain passivity- based solutions [3, 6, 11], or wave-variable passivity-based ap- proaches [9, 10]. But the proposed approaches assume constant network delays [6], or delays with small variability [3, 6, 9–11]. Such assumptions on the network delay do not apply for robots connected using IEEE 802.11 wireless technology, which suffers from uncontrolled packet losses and delays. Specially in industrial scenarios with electromagnetic interference jamming the wireless channel. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). SIGCOMM ’22 Demos and Posters, August 22–26, 2022, Amsterdam, Netherlands © 2022 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-9434-5/22/08. https://doi.org/10.1145/3546037.3546047 Wi-Fi 1 2 3 4 5 6 Packet loss FoReCo 4 1 2 3 5 6 Forecast Drivers Internet Remote Controller control commands Figure 1: FoReCo forecasts/infers control commands lost in the wireless communication between the remote controller and the robotic arm. 2 FORECO SOLUTION Rather than making assumptions on the network delays, we propose FoReCo [4], a Forecast recovery mechanism for Remote Control that infers lost/delayed control commands. FoReCo feeds the ro- bot drivers with the lost/delayed commands it recovers through forecasting – see Figure 1. FoReCo receives the remote control commands and checks if they are received at the expected frequency, e.g., each 150ms. In case a command does not arrive on time (due to 802.11 collisions or interference not recovered with error-correction), FoReCo fore- casts/infers the out of time command using the recent command history. In this demonstration FoReCo uses a multinomial logistic re- gression that we train using a real-world dataset of an experienced robotic arm operator. The ML model receives as input: (1) the posi- tion of each joint 𝑗𝑖(𝑡), ∀𝑖; (2) for how long each joint has been mov- ing without stopping max𝑡0<𝑡{𝑡−