Industrial businesses recognize the critical role of a website in their operations. A single online platform can effectively manage multiple key business functions. These essential functions include capturing potential leads and attracting new customers. Furthermore, the site should serve to showcase the company's industry expertise. Finally, it can be used to organize and streamline customer service activities.
Jaiveer Singh focuses on foundational aspects of robotics rather than just impressive demonstrations. His expertise lies in the necessary infrastructure, including the internal circuit boards and supporting software. He develops tools that allow developers to process data from robot cameras. Moreover, he tackles the complex engineering required for robots to move beyond controlled test environments. Essentially, his work accelerates the practical deployment capabilities of robotics technology.
X Square Robotics utilizes a comprehensive system integrating foundation models, specialized robotics hardware, and a robust data pipeline. This technology is designed for successful real-world deployments across various applications. Following four consecutive funding rounds, the company's valuation has reached $2.8 billion. Information regarding this achievement was initially reported by The Robot Report.
Queue is developing automated pharmacy units designed to improve prescription accessibility. These advanced systems aim to operate autonomously across various locations. Deployment sites will include hospitals, retail stores, and medically underserved communities. Recent reporting confirms that Queue has successfully raised necessary funding for this expansion. The development focuses on bringing routine medication access to a wider public reach.
Morph has unveiled a novel, physically intelligent soft robotics platform. This technology allows for the design and manufacture of components called "soft robotic cells." These cells are intended to embed artificial intelligence directly into physical hardware. The initial announcement regarding these advanced cells was published by The Robot Report.
Three MIT teams achieved significant success at the 2026 NASA RASC-AL Competition. They earned a total of five top awards during the event. The competition focused on developing essential components for lunar bases. Furthermore, the teams addressed designs necessary for upcoming missions to Mars. Their achievements highlight student ingenuity in aerospace engineering.
The ros2_canopen stack natively integrates CANopen devices into ROS 2 by utilizing lely-core for low-level protocol handling. It allows developers to configure a CAN bus through a single YAML description, launching the master and device drivers accordingly. Users can operate in standard nodes, lifecycle nodes, or integrated with ros2_control for control tasks. The stack offers two drivers: a generic Proxy Driver and a specialized CiA 402 driver for motion control. Recent updates enhance multi-drive coordination, enabling single nodes to represent multiple axes as individual joints controllable through familiar ROS 2 controllers.
Truck-drone delivery leverages smart lockers as automated hubs for drone docking, parcel exchange, and battery swaps, enhancing service range. Addressing real-world complexity, this research proposes a locker-based truck-drone routing problem integrating pickups, deliveries, and no-fly zones (LTDRP-PDNF). The goal is to minimize operational cost for the entire fleet using integrated routing. The method models route construction as a Markov Decision Process solved by a two-stage deep reinforcement learning heuristic. This system first solves the truck-only routing via an attention encoder/BiGRU decoder and then combines this with a hybrid heuristic for final, coordinated truck and drone paths.
Vision-Language-Action (VLA) systems excel on robot manipulation tasks, leading to interpretations that suggest semantic understanding translates directly to physical capability. However, this paper argues that such generalization is unverified because current evaluation metrics cannot distinguish between semantic mapping and actual physical decision-making. Task success rates are insufficient because improvements could stem from various sources like distributional overlap or mere pattern matching. The authors propose novel evaluation designs that introduce controlled variation to causally separate and measure semantic versus physical generalization abilities. This approach aims to clarify when claims of physical competence derived from VLM backbones can be meaningfully assessed.
Robotic endovascular guidewire navigation requires accurate control in complex patient anatomies, but current methods fail due to static reward functions lacking context awareness. This paper introduces a Vision-Language Procedural Reasoning (VL-PR) framework designed to address these limitations. The core of the system integrates a multimodal large language model (MLLM) that interprets real-time visual data to infer high-level procedural contexts. These inferred insights are then used for context-aware reward adaptation, dynamically adjusting component importance across different navigation phases. Testing on physical robotic platforms demonstrated that this approach significantly enhances task reliability and efficiency compared to static reward methods.
Existing large-scale dexterous grasp datasets primarily support grasp generation and simple pick-and-place tasks. Researchers adapted these datasets to foster functional dexterity for articulated tool use, requiring tools to be acquired, maintained, and operated. A hierarchical imitation learning framework was developed, utilizing a new 355k-trajectory dataset derived from existing grasp annotations. This low-level controller was pretrained on the grasp data and fine-tuned on specific task demonstrations within the introduced DexCraft benchmark. Evaluations showed that this method outperforms end-to-end diffusion policies in both simulation and real-world tasks, proving grasp datasets are useful for advanced contact manipulation training.
Wind velocity estimation using quadrotors is challenging due to the system's high nonlinearity. This study evaluates both continuous and discrete dynamic equations on the SE(3) manifold for this estimation task. A Lie Group Variational Integrator provides a discrete model without approximation errors. Performance was assessed using Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) in simulations and outdoor flights. Results show that coupling discrete SE(3) dynamics with UKF achieves superior wind velocity estimation accuracy while maintaining trajectory tracking, even with low-cost sensors.
Presents TAPE, a novel method for autonomously exploring unknown three-dimensional cavities using a tethered aerial robot. The approach minimizes both traveled distance and unwound tether length by utilizing a two-level hierarchical architecture. Global planning solves a Traveling Salesman Problem (TSP) to minimize distance efficiently. Local planning further optimizes the path cost and tether length using an adjustable decision function for trade-off management. Simulations show TAPE generates only a 4.1% greater distance than pure TSP while ensuring the tether remains below its limit in 100% of simulated cases compared to 53% without it.