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0111 · Jan 201919922001200920172026
6 results for quadcopters

Researchers develop multi-agent systems for quadcopters to collaborate in missions.

problem Enable multiple quadcopters to work together in remote sensing tasks.
method Agent dynamics, network topologies, collective behaviors, agreement protocol, equations of motion for quadcopters.
result Multi-agent systems can successfully collaborate in remote sensing missions.

This work improves motion planning for quadcopters by learning and reasoning about controller performance.

problem Improving motion planning for quadcopters with safety margins and execution reliability.
method Introspective learning and reasoning to correct execution bias and improve collision checking.
result Substantial reduction in safety margins for motion actions, leading to safer execution.

The paper shows why AI safety doesn't generalize across tasks.

problem AI safety fails to generalize across unseen tasks.
method Theoretical analysis of linear-quadratic control with HH_{\infty}-robustness, empirical demonstrations in simulated quadcopter navigation and CRM.
result The mapping from task specification to an optimal controller has a higher Lipschitz constant with safety requirements than without, indicating inherent complexity of safety.

Imitation learning is a control design paradigm that seeks to learn a control policy reproducing demonstrations from expert agents. By substituting expert demonstrations for optimal behaviours, the same paradigm leads to the design of control policies closely approximating the optimal state-feedback. This approach requ…

2019-01-07abs ↗pdf ↗