Wireless Communication in Robotics

With the current impact of cell network outages across almost all carriers in the US, it's a good time to talk about the future; actually, it's not even about the future, it's the present. Several years ago I started talking about having mobile robotics (air, ground and maritime robotics, like drones, rovers and submergible devices) be part of a mobile adhoc network or MANET. One example is a private mesh network, like Silvus Technologies provides. These communications solutions for high bandwidth video, C2, health and telemetry data are absolutely needed in today's environment and allow for a very flexible set-up and coverage; from a local incident scene, to a much larger area coverage, to entire cities or counties being covered. Why the need? While we in the drone industry originally focused on getting drones connected to a cell network, we quickly realized the single point of failure; the cell network infrastructure. Natural disasters, as well as manmade disasters, can impact these networks dramatically. An earthquake, hurricane, a solar storm, or a cyberattack, can take down these public networks for hours to days. And that includes public safety dedicated solutions like FirstNet or Frontline, during times when coms and data push is absolutely needed. Over the past couple of years we have seen the rise of mobile robotics deployments within private networks. While the defense side has done this approach for years, the public safety sector is still new to this concept. Some solutions integrate with a variety of antennas, amplifiers and ground stations, offer low latency, high data rates (up to 100+Mpbs), 256-bit AES encryptions and allow for a very flexible and scalable mobile ad-hoc mesh network solution. And most importantly - independence from a public network system. And now imagine you have multiple devices operating; a helicopter, a drone, a ground robotic, together with individuals on the ground, all connected and all tied into a geospatial information platform, like ATAK/TAK. Each connected device can become a node and extend the range. This is what I am calling building the Tech/Tac Bubble. This is not just the future, this is already happening with a handful of agencies across the US It's time to start thinking about alternative communication solutions and mobile robotics are an important part of leading the way. #UAV #UAS #UGV #Drones #network #MANET #Meshnetwork #publicsafety

I spent the last year and a half building autonomous systems for orchards at Bonsai Robotics. The biggest surprise? Connectivity is the infrastructure problem nobody talks about. Everyone focuses on the robotics—the perception systems, the path planning, the manipulation. But when you're operating in a 500-acre almond orchard in Australia or the Central Valley, you're dealing with spotty cellular coverage, dust that degrades signal quality, and distances that make WiFi impractical. The robots can see. They can navigate. They can make decisions. But if they can't reliably communicate with fleet management systems or push telemetry data for analysis, you're running blind. This isn't just an ag problem. I've seen similar challenges in all off-road and remote applications, including marine robotics with Wave Gliders operating thousands of miles offshore, army tanks on the frontlines, and rail vehicles and trucks in rural ODDs. The solution isn't just "add more cellular towers." It requires edge computing architectures that let vehicles operate autonomously when connectivity drops, smart data prioritization that pushes critical telemetry first, and mesh networking between vehicles to create resilient communication networks. Connectivity infrastructure is as important as the autonomy stack itself. You can't deploy at scale without solving both. What connectivity challenges have you seen in deploying hardware in remote environments?

Our new publication on: “ A Fully Self-Powered Triboelectric Wireless Sensor for Robotic Arm Control via Efficient Electromagnetic Induction”, Nature Sensor; https://lnkd.in/gWBEPB9z The human arm, as an ultra-precise mechanical system, can perform complex and delicate movements. Using wearable sensors to control bionic robot arms represents a revolutionary advancement in industrial robotics. However, conventional wearable wireless sensors typically rely on battery power and wireless modules, leading to limited lifespan, environmental concerns, and increased system complexity. In this paper, we propose a fully self-powered wireless arm interface (SWAi), featuring a self-powered arm motion sensor (SAMS) via efficient electromagnetic induction and strongly coupled magnetic resonances (SCMR). SAMS employs a double-layered ternary electrification sliding triboelectric nanogenerator as the mechanical-to-electrical energy conversion module. With a compact slider (20 × 33 mm2), it generates 608 μJ of energy per motion cycle, sufficient to power both signal generation and wireless transmission over industrially relevant distances via magnetic induction. Notably, the entire process of sensing and communication is driven solely by the mechanical energy of arm movement. The SWAi enables intuitive, battery-free control of robotic arms, showing significant potential for industrial robotics and human-machine interaction.

New article with Gerasimos Damigos on "5G-enabled robots: Differentiated connectivity for varying mission requirements through dynamic QoS" published in the IEEE Transactions of Vehicular Technology. Link: https://lnkd.in/dc9btUJ5 The fifth generation (5G) cellular network technology has matured and is increasingly utilized in many industrial robotics applications. Various sectors seek to harness the advanced communication performance and deploy time-critical robotic applications in a connected manner, often hosting the execution of computational intensive time-critical components in the edge cloud. Robust deployment of cellular enabled robots that rely on the network performance demands the utilization of quality of service (QoS) solutions to respect the real-time requirements of critical applications. This paper proposes a method of harnessing the 5G QoS features in a dynamic fashion to retain the time-critical requirements of the edge-offloaded robotics applications. The paper emphasizes the dynamic selection of network resources considering the continuously changing communication requirements of such applications based on the underlying evolving mission and highlights the importance of deploying offloaded robotics applications to be communication aware — towards the era of co-design. Further, the dynamic nature of the background network traffic is examined and robot scalability with varying mission priorities is analyzed and discussed. A novel modeling approach coupling the time-critical performance of 5G-enabled robotics and the dynamic QoS selection is presented and utilized in the selection of the appropriate QoS profile. The lack of real-life evaluation of complete similar solutions is tackled by extensive experimental evaluation utilizing a real-life 5G stand alone (SA) network and a quadruped robot. The obtained results demonstrate the importance of such synergistic solutions. #robotics #5G #6G #autonomy #AI #control

We’ve operated robots over 150,000 miles from our Robotic Security Operations Center in Pennsylvania --- and one of the most common questions I get is about wireless connectivity. So, how does it work? It ranges from quick setups that get us fully connected in under 5 minutes to more technical configurations like the one shown in the video below. In this example, we were operating in GPS-denied, communications-limited tunnels, which required a more advanced setup. We deployed a mesh network of Persistent Systems, LLC radios within the tunnel network, using Starlink as a backhaul for video, telemetry, and command & control (C2). From there, we monitored automated missions from the safety and comfort of our operations center --- leveraging robotic technology as an extension and augmentation of our team. For the majority of our operations, though, it’s as simple as powering on the robot. We leverage secure cellular connectivity to provide instant access to live video, telemetry, and C2 through our cloud-based platform. By bringing our own network wherever we go to connect and operationalize drones and robots for clients, we’ve seen incredibly fast speed-to-value across deployments. I love solving problems with technology, and there's almost always as solution to get systems deployed and creating value on-site quickly. #robotics #robots #connectivity

📡 Deterministic Wireless: 12 Practical Rules to Eliminate Jitter Deterministic Wireless isn’t about low latency. It’s about eliminating jitter, the real enemy of industrial automation. In factories, robotics, digital twins, and real-time AI, even “fast internet” fails when packet timing fluctuates. That’s why deterministic wireless follows a very different playbook. Here are 12 practical rules to eliminate jitter 👇 1️⃣ Measure jitter first (not just latency) Track packet delay variation (PDV). Averages hide the spikes that break systems. 2️⃣ Define jitter budgets per workload Robotics, control loops, and video all tolerate jitter differently. Design accordingly. 3️⃣ Classify traffic into real-time classes Without traffic classes, real-time flows compete with everything else, and lose. 4️⃣ Reserve bandwidth for critical flows Background traffic should never steal capacity from control systems. 5️⃣ Use deterministic scheduling (not FIFO) FIFO creates randomness. Deterministic scheduling enforces timing guarantees. 6️⃣ Enforce QoS end-to-end QoS must span AP/RAN, switches, routers, gateways, and edge links, gaps create jitter. 7️⃣ Fix roaming to prevent micro-dropouts Most jitter spikes come from handover gaps. Tune overlap and fast transitions. 8️⃣ Treat RF interference as a system dependency Retries and collisions add delay. Interference must be actively managed. 9️⃣ Avoid wide channels in dense environments Wider isn’t better. Narrower channels are more predictable and stable. 🔟 Use redundancy: MLO / multi-path reliability Multiple paths reduce hotspots and absorb sudden delay spikes. 1️⃣1️⃣ Place compute at the edge Cloud round-trips add unpredictability. Edge inference keeps control loops tight. 1️⃣2️⃣ Close the loop with AI-driven RF optimization Static tuning fails in real life. AI detects jitter and adjusts in real time. The big takeaway? Deterministic Wireless isn’t about maximum speed. It’s about predictability. Because in industrial networks, consistency beats peak throughput, every single time. 👉 Follow Abhishek Singh for insights on Deterministic Wireless, Wi-Fi 7, Private 5G, and AI-native connectivity. #DeterministicWireless #IndustrialNetworking #WiFi7 #Private5G #EdgeAI #AutonomousNetworks #IndustrialAI

Robots, AI, and real-time control: Why Korean factories are betting big on Private 5G — and what the world can learn from it. South Korea may have been the first to launch nationwide 5G, but the real revolution isn’t in smartphones — it’s happening on factory floors where autonomous robots, vision-based quality control, and AI-driven operations demand more than Wi-Fi can handle. Key takeaways from the latest TeckNexus interview with Prof. Seong-Lyun Kim (Eric) of Yonsei University and Mika Skarp from Cumucore: 🚀 Dedicated mid-band spectrum (4.7 GHz), reserved exclusively for industrial use to guarantee performance without competing with consumer traffic. 🤖 Robots that don’t drop connections, from autonomous forklifts to robot baristas that talk to customers, seamless mobility and robust uplink make Private 5G a game-changer. 💡 Flexible pricing & Network-as-a-Service, factories, especially SMEs, need plug-and-play solutions that cost no more than upgrading Wi-Fi. 🏭 Edge + AI-native future, tomorrow’s networks won’t just connect machines, they’ll run AI workloads, manage slices, and adapt on the fly — zero human intervention. South Korea’s playbook shows that clear policy, practical spectrum, and real ROI are key to making Private 5G more than hype. 👉 Watch the full discussion and see live robot demos here: https://lnkd.in/gJciqvvT 🔍 How is your factory approaching wireless upgrades? What’s holding you back? Let’s exchange ideas in the comments! #Private5G #SmartManufacturing #Industry40 #AI #5G #Cumucore #YonseiUniversity #Robotics #EdgeAI #PrivateNetworks #Robots