5 accepted papers
Recognition of human manipulation actions in real-time is essential for safe and effective human-robot interaction and collaboration. The challenge lies in developing a model that is both lightweight enough for real-time execution and capable of generalization. While some existing methods in the lit
An autonomous service robot should be able to interact with its environment safely and robustly without requiring human assistance. Unstructured environments are challenging for robots since the exact prediction of outcomes is not always possible. Even when the robot behaviors are well-designed, the
Robots are more capable of achieving manipulation tasks for everyday activities than before. However, the safety of manipulation skills that robots employ is still an open problem. Considering all possible failures during skill learning increases the complexity of the process and restrains learning
We need robots more aware of the unintended outcomes of their actions for ensuring safety. This can be achieved by an onboard failure detection system to monitor and detect such cases. Onboard failure detection is challenging with a limited set of onboard sensor setup due to the limitations of sensi…
Handling safety is crucial to achieve lifelong autonomy for robots. Unsafe situations might arise during manipulation in unstructured environments due to noises in sensory feedback, improper action parameters, hardware limitations or external factors. In order to assure safety, continuous execution…