Ali-akbar Agha-mohammadi
نویسنده
چکیده
Broad research interests and related applications: My research is in the area of stochastic systems, computational methods for sensing, estimation, and control problems, with a focus on robotic systems. In real-world systems, uncertainty (both in the system model and sensory readings) is omnipresent. A few of the vast set of applications for this research include (i) Motion planning for mobile robots and manipulators under uncertainty, (ii) precise control of medical robots under imperfect measurements, (iii) multiagent cooperation and coordination under stochastic communication, and (iv) planning for robots aiding healthcare operating in changing and uncertain environments with people.
منابع مشابه
On the Probabilistic Completeness of the Sampling-based Motion Planning Methods Under Uncertainty
This paper extends the concept of probabilistic completeness defined for the motion planners in the absence of noise, to the concept of “probabilistic completeness under uncertainty” for the motion planners that perform planning in the presence of uncertainty. According to the proposed definition, an approach is proposed to verify the probabilistic completeness under uncertainty. Finally, it is...
متن کاملDynamic Closed-loop Replanning in Belief Space: Toward Handling Dynamically Changing Environments
Motion planning in belief space is a challenging problem due to the computational intractability of its exact solution. This problem becomes even more challenging in changing environments. This paper proposes a dynamic replanning scheme in belief space to handle changes in the environment (e.g., changes in the obstacle map), as well as unforeseen large deviations in the robot’s location (e.g., ...
متن کاملProbabilistic Completeness of the Belief Space Motion Planners
This paper extends the concept of “probabilistic completeness” defined for the motion planners in the state space (or configuration space) to the concept of “probabilistic completeness under uncertainty” for the motion planners in the belief space. Accordingly, an approach is proposed to verify the probabilistic completeness of the sampling-based planners in the belief space. Finally, through t...
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