10 accepted papers
Active delivery of food to a human mouth in a controlled and safe manner remains a key challenge for robot‑assisted feeding systems (RAFSs). Existing RAFS designs struggle to simultaneously achieve efficiency and safety: rigid manipulators offer fast and accurate motion but risk hazardous contact, w…
Active delivery of food to a human mouth in a controlled and safe manner remains a key challenge for robot-assisted feeding systems (RAFSs). Existing RAFS designs struggle to simultaneously achieve efficiency and safety: rigid manipulators offer fast and accurate motion but risk hazardous contact, w
Articulated objects are ubiquitous in daily environments, and effective manipulation of these objects is essential for advancing open-world robotics. Existing approaches, which rely heavily on large-scale data collection or simulation, often face limitations in real-world applications, including iss
Dual-arm robotic systems hold great potential for complex bimanual tasks that require intricate and coordinated manipulation, such as holding and transporting a tray with a cup of coffee while navigating through cluttered environments. However, these tasks pose significant challenges due to the inhe
The data-driven paradigm has shown great potential in solving many decision-making tasks. In the robot navigation realm, it also sparked a new trend. People believe powerful data-driven methods can learn efficient and general navigation policies from a vast offline dataset. However, robot navigation
Reinforcement learning has shown great potential in improving the performance of robot navigation. In response to the increasing deployments of mobile robots within various scenarios, a data-driven paradigm of navigation approach with safety verification is preferred where one can train RL algorithm…
Robot navigation using deep reinforcement learning (DRL) has shown great potential in improving the performance of mobile robots. Nevertheless, most existing DRL-based navigation methods primarily focus on training a policy that directly commands the robot with low-level controls, like linear and an…
Autonomous mobile robots have become popular in various applications coexisting with humans, which requires robots to navigate efficiently and safely in crowd environments with diverse pedestrians. Pedestrians may cooperate with the robot by avoiding it actively or ignoring the robot during their wa
Existing navigation policies for autonomous robots tend to focus on collision avoidance while ignoring human-robot interactions in social life. For instance, robots can pass along the corridor safer and easier if pedestrians notice them. Sounds have been considered as an efficient way to attract the…
It is challenging for a mobile robot to navigate through human crowds. Existing approaches usually assume that pedestrians follow a predefined collision avoidance strategy, like social force model (SFM) or optimal reciprocal collision avoidance (ORCA). However, their performances commonly need to be…